Isolated neutron stars offer a unique laboratory that encompass aspects of plasma physics, general relativity, fundamental physics and magneto-hydro-dynamics, within extreme conditions of density, magnetic field and gravity. The physics of neutron stars can be studied through the radio and high-energy information provided by these compact objects. 
The project aim at exploiting the new in-house developed 3D code MATINS (MAgneto-Thermal evolution of Isolated Neutron Stars), available at https://github.com/ice-csic-astroexotic/MATINS . The code is considered by the community as the state-of-the-art in terms of coupled roto-magneto-thermal evolution with the most realistic microphysical ingredients available. The methodology consists in exploring the evolution of rotational properties, magnetic field and temperature for different initial configurations, stemming from the 20-years-long expertise of the groups in Barcelona and Alicante, involved in its continuous development. The student will expand on recent and on-going works, by understanding the general context, the main ingredients of the code, and running it in local clusters. The results will embark a variety of different aspects with direct comparison with observations, related to both rotational properties (spin period and their time derivatives), and thermal emission from the surface as seen in X-rays.
If you are interested, have a look of our recent works, e.g.: https://arxiv.org/abs/2305.06342 , https://arxiv.org/abs/2509.06699 , https://arxiv.org/abs/2605.08068 and https://arxiv.org/abs/2609.17436.

Since the launch of SDSS, our understanding of galaxy formation has advanced dramatically. Tight scaling relations, such as the size-mass relation and the luminosity-velocity dispersion relation for early-type galaxies, have emerged as key observational evidence supporting the hierarchical model of galaxy formation. Yet despite this broad picture, the details of how baryonic processes shape galaxy formation remain poorly understood. Upcoming and ongoing surveys, including SDSS, the DESI Legacy Imaging Survey, and the future LSST, will soon deliver galaxy samples of unprecedented size, offering a unique opportunity to test and refine our understanding of these scaling relations. However, extracting reliable physical insight from such large datasets is far from trivial, and AI agents are emerging as powerful tools to help identify meaningful physical trends hidden within massive catalogs. In this study, we will use Denario, an AI agent developed by astronomers, to revisit galaxy scaling relations using data from the DESI Legacy Imaging Survey. The student will learn to process large-scale astronomical survey data and to collaborate with an AI agent throughout the analysis pipeline, developing both a solid foundation in galaxy formation physics and the critical skill of verifying and interpreting AI-generated results.

Galactic gamma-ray transients are extremely rare (about 10 known sources), and very hard to find. The Fermi-LAT All-Sky Variability Analysis (FAVA) flags about one genuine Galactic flare per year with no counterpart in any catalog, which remains unidentified due to poor localization. That is, the LAT can only constrain the position to a large degree-scale region that, in the crowded Galactic plane, contains hundreds of potential counterparts. Rapid follow-up at another wavelength is the only proven way to associate these events (typically in X-rays) but it requires the transient to still be active when the X-ray observations are approved.

The objective of this project is to test whether the Rubin Observatory's Legacy Survey of Space and Time (LSST) can remove that constraint. Because LSST surveys the whole sky every few nights, it provides both a contemporaneous optical alert for gamma-ray flares, and a uniform archival record for all sources. The student will develop a pipeline that cross-matches FAVA transient regions against LSST alerts and light curves, calibrate the chance-association rate using field-density simulations, and apply it to the known unassociated FAVA sample. A positive result would open a completely new channel for discovering flaring Galactic particle accelerators. Should a Galactic transient occur during the project, the student will have the opportunity to propose Target-of-Opportunity observations with X-ray and radio facilities.

The majority of supermassive black hole (SMBH) growth is thought to occur during very obscured phases, when the accretion flow is hidden by the circumnuclear gas and dust known as the "torus." Its properties (geometry/clumpiness, density, dynamical state) govern how efficiently the black hole is fueled, but they remain largely unknown. Current X-ray torus models are calibrated on spectra of obscured active galactic nuclei (AGN, accreting SMBHs) but treat the obscuration as static. They use no variability information, even though changes in obscuration are a direct probe of the size and location of the absorbing gas.

This project is part of a broader effort to develop a torus model constrained by the time domain: how often the line-of-sight obscuration changes around SMBHs, and by how much. The student will learn how to perform broad-band X-ray spectral analysis of a sample of AGN with archival XMM-Newton, Chandra, and NuSTAR observations. Fitting physical torus models epoch by epoch, they will measure obscuration and its variability, turning cloud-eclipse events into constraints on the size, density, and orbital radius of the obscuring clouds relative to the accretion disk and broad-line region. The resulting measurements will enlarge the sample used to calibrate torus models.

Around every galaxy lies an extended, ghostly stellar halo that records every merger and accretion event the galaxy has ever experienced. Characterising the properties of these halos is therefore essential to understanding how galaxies assemble over cosmic time. However, this component is so faint that it remains extremely difficult to observe, and as a result we still know remarkably little about its properties. In this thesis, we will use cosmological simulations to determine how to reliably measure this elusive component, deriving its light profiles, colours, and total luminosity in order to build a complete picture of stellar halos and to guide the interpretation of real observations

The space between galaxies in a cluster is filled with an extremely diffuse, ghostly light called the intracluster light (ICL). This light is formed by stars stripped from galaxies during interactions, left drifting freely between them. Because the ICL forms and grows through mergers and interactions, its distribution carries a fossil record of the cluster's dynamical history: whether the cluster is old and relaxed, or young and still merging. This project will use cosmological simulations, where the true dynamical state of each cluster is known, to characterise the morphology of the ICL and design a new metric that directly links ICL shape to dynamical state. Such a metric would provide a purely photometric way to classify a cluster's dynamical state straight from deep imaging. This is essential for the hundreds of thousands of clusters that next-generation surveys will image, for which detailed follow-up will not be possible.

One of the most intriguing structures found in the nearby universe is a trail of a dozen ultra-diffuse galaxies in the NGC 1052 group, aligned as if born from a violent collision between two gas-rich dwarf galaxies. This appealing picture is supported by the fact that some of the trail's members show a negligible dark matter content and, in one of the galaxies, signs of ongoing tidal disruption. However, other properties are difficult to reconcile with this single, shared formation event, and raise the question of whether all these galaxies genuinely belong to the same family. Ultra-deep imaging offers a direct way to settle this: by characterising in detail the light profiles and the faint, outer regions of each galaxy in the trail, we can test whether they share the same structural properties or whether some are simply unrelated interlopers caught in projection. This work will determine whether this enigmatic trail is a genuine fossil relic of a dwarf-dwarf collision or an illusion created by chance alignment.

Massive black holes (>1e6 Msun) are expected to reside at the centres of most massive galaxies in the Universe, and a broad range of observational evidence supports a close connection between these objects and the properties of their host galaxies, such as stellar mass, luminosity, and morphology. These correlations point toward a co-evolution scenario in which galaxies and their central black holes grow together over cosmic time. Despite this general framework, a population of overmassive black holes has been identified that challenges standard evolutionary models. Their rapid assembly, particularly at high redshift, is still not well understood and represents an important open question in models of black hole and galaxy formation. Galaxy mergers add further complexity to this picture. When two galaxies interact and merge, their central massive black holes are expected to sink toward the centre of the remnant through dynamical processes, eventually forming a gravitationally bound system known as a massive black hole binary (MBHB). These binaries are among the most promising sources for current and future gravitational-wave observatories, including Pulsar Timing Arrays (PTAs) and the Laser Interferometer Space Antenna (LISA). In addition to their gravitational-wave emission, massive black hole binaries may also produce electromagnetic signatures, making them key targets for multimessenger astronomy. The combined detection of gravitational and electromagnetic signals would provide a unique window into the physics of black hole mergers and their surrounding environments.

In this work, we aim to investigate the diversity of single massive black holes, explore the formation pathways of massive black hole binaries, and assess their detectability through electromagnetic signatures. To do so, we employ a combination of semi-analytical models and cosmological hydrodynamical simulations, which together offer complementary perspectives on the growth and evolution of black holes in a cosmological context.

Spanish contribution -the Science Diagnostics Subsystem- to LISA, the future space-borne gravitational wave detector with expected launch in 2035. A particular interesting challenge arising in LISA and other fundamental physics space missions is the high stability control of temperature in the very low-frequency range (below the milliHertz). Our group is currently developing the techniques with potential impact in these future missions. For that purpose we are investigating temperature sensing by means of phase locking to optomechanical resonators. 

In our lab, a temperature sensor in the nano-Kelvin precision regime is being developed using optical systems, for its applications in Gravitational wave detection. The main element is a Whispering Gallery Mode (WGM) resonator which will serve the purpose of an optical cavity that provides time stability in the low frequency domain. The resonator itself can be used as a temperature sensor.

The Pound-Drever-Hall technique (PDH) is used to stabilize the Laser (which is the source of light for the resonator) in frequency, using the direct outputs of the Cavity (WGM resonator). To implement this technique, a frequency modulated beam is locked to a cavity. The output of this beam is measured and down mixed with an oscillator (in phase with the frequency modulation of the beam) to obtain the “off resonance” of the laser with respect to the cavity. This way a feedback loop can be implemented to correct the laser frequency towards resonance with the cavity, in our case, the WGM resonator.

The candidate work will consist of the development, characterization and optimization of the feedback control loop of the PDH technique, and apply it to an existing optical setup working in ultra-stable regime. The objective is the characterization of the PDH lock at low frequencies and the optimization of the parameters of the experiment to achieve nano-Kelvin performance down to the millihertz measuring bandwidth.

The Gravitational Astronomy group at the Institute of Space Sciences (ICE-CSIC) is leading the Spanish contribution -the Science Diagnostics Subsystem- to LISA, the future space-borne gravitational wave detector with expected launch in 2035. Our group is also leading the design of an In-Orbit Demonstrator (IOD) selected to fly in the forthcoming cubesat of the Generalitat de Catalunya New Space strategy (expected launch 2026).

The objective of ILIADA (In-orbit LISA diagnostics demonstrator) is to place in orbit novel technologies that are being developed for the detection of gravitational waves in space and to test them in a LEO environment with the aim, also, to put to test noise characterisation and subtraction algorithms. ILIADA will consist of high-precision temperature sensors, magnetometers and a radiation monitor that will represent a first version of the future LISA diagnostics system.

The magnetometers signal on-board ILIADA will be dominated by the space-craft and the Earth magnetic field contribution. The candidate work, in collaboration with the ILIADA multidisciplinary team, will be to develop data analysis methods that allow the subtraction of these contributions. The aim of the work is to enable ILIADA to detect Earth magnetic field features, as the so-called Birkeland currents. These methods are expected to have an impact in the future LISA instrument characterisation pipelines.

LISA (Laser Interferometer Space Antenna) will be the first gravitational‑wave observatory in space. The mission requires an extremely stable in‑flight environment to detect signals at millihertz frequencies. To guarantee this stability, the Science Diagnostics Subsystem monitors temperature, magnetic fields, and radiation around the gravitational reference sensors and optical benches. Its correct operation is essential both for interpreting the scientific data and for ensuring that environmental fluctuations remain well below mission requirements.

This project focuses on the on‑ground validation of the Elegant Bread Board Model (EBBM) of the Diagnostics Subsystem. The EBBM integrates the Data Acquisition Unit (DACU), together with representative temperature sensors, magnetic sensors, and the radiation monitor. The student will participate in the full chain of functional and performance verification, working alongside the ICE‑CSIC team responsible for Spain’s contribution to LISA diagnostics.

The training will include hands‑on work with laboratory instrumentation, execution of measurement procedures, and acquisition of sensor data under controlled thermal, magnetic, and radiation conditions. The student will help characterize sensor sensitivity, bandwidth, and low‑frequency stability, evaluate the end‑to‑end performance of the DACU, and compare measurements with mission requirements and existing simulations. They will also contribute to data processing using Python tools commonly applied in space‑instrumentation testing.

This project offers an excellent introduction to precision instrumentation for space science, providing direct involvement in a subsystem with a key role in ESA’s flagship gravitational‑wave mission. The student will gain laboratory experience, data‑analysis skills, and insight into the workflow of space‑qualification activities within an international collaboration.

Asteroids are usually covered by fine grained, collisionally processed regolith, changing the reflectance properties of these challenging bodies. We will work with chondritic meteorites: thick sections and grinded materials as the best proxies to simulate asteroid surfaces.

The experiments will be taken using a Brucker VIS-NIR spectrometer under vacuum at the ICE-CSIC Meteorite and Sample Return clean laboratory, where the reflectance
spectra will be taken in different modes and spectral windows. We will use these laboratory spectra to compare with the spectra of real asteroids, identifying from
the absorption bands and features the main rock-forming minerals and processes at work in interplanetary space.

Microquasars are binary systems composed of a compact object and its stellar companion. The compact object, either a black hole or a neutron star, is constantly accreting plasma from the star -- forming a relativistic jet that can extend up to several parsecs. Interestingly, due to the presence of internal shocks or through its interaction with the interstellar medium, this jet can act as a powerful astrophysical particle accelerator. As the origin of Galactic cosmic rays is unknown, that could imply that a significant portion of cosmic rays originate in microquasars, a hypothesis supported by recent gamma-ray observations. But then, a population large enough should exist. Where are they? And how many do exist? The objective of this project is to identify this new population of particle accelerators using gamma-ray observatories.

Participating in this project, you will learn how to analyse real gamma-ray data from the Large Area Telescope on board the Fermi satellite (Fermi-LAT) using maximum-likelihood, time series, and Monte Carlo statistical methods. In particular, you will identify the best candidates according to multi-wavelength data and search for gamma-ray emission caused by cosmic-ray bubbles around microquasars, or gamma-ray flashes during powerful flares of their jets. The results will be contextualised with one-zone hadronic and leptonic models of the most plausible emitting regions within and around microquasars. Note: following the student's preference, an alternative project of a similar nature could also be applied to supernovae.

The thermodynamics of the Solar atmosphere can be probed in detail at millimeter and submillimeter wavelengths (300 microns to 1 cm; 30-1000 GHz), revealing information difficult to obtain at any other wavelength (see https://ui.adsabs.harvard.edu/abs/2025OJAp....8E.129K/abstract).  Here at ICE-CSIC, we are building a novel mm-wave spectrometer (~90 GHz) for solar and atmospheric observations, coupled to power diode sensors.  The student will work on the electronics and programming to measure the signals from these sensors, building on knowledge of electronic circuit design and testing (instrument amplifiers, analog to digital converters), as well as embedded system programming (e.g. with a Raspberry Pi and Arduino boards), likely following a methodology similar to that outlined in https://arxiv.org/abs/2602.23338 (section III).  Further opportunities exist for testing and field work, using the hardware for real solar and atmospheric measurements. This project involves an exciting and potentially fun mix of both design and hands-on experience, and just needs a motivated student with some background in electronics and programming and an interest in astronomy!

We propose a range of topics based on forecasting and determining the capabilities of AtLAST using maria (https://github.com/thomaswmorris/maria), ranging from exploring nearby objects like the Galaxy, Magellanic Clouds, external galaxies both nearby and far into the early universe, and the overall large scale structure of the universe, including the cosmic microwave background radiation from the Big Bang itself. We also propose developing fundamental technical capabilities for the telescope, such as instrumental properties, polarization, and spectroscopy. And finally, we propose development of data analysis and handling methods like machine learning through Gaussian processes (nifty denoising; see https://github.com/jwuerzinger/CMB_denoising), maximum likelihood mapmaking to process polarization and 3D spectral data cubes, and pipeline development to process the massive amounts of data that AtLAST and its precursors will generate. If any of the above areas interest and excite you, we are open to explore the possibilities and converge on an interesting subset of the many topics outlined above.

Characterization of exoplanets requires high instrumental precision as well as combining measurements from very different sources in a common framework. In addition to this, numerous instrumental and astrophysical degeneracies exist so interpreting this high quality data requires holistic and unbiased techniques to combine all the data consistently. Although we can simulate most of the complexity of the observations, these degeneracies are often difficult to predict a priori, creating all sorts of false negative and false positive detections of exoplanet features.

To account for this, and to accommodate the increasing complexity of astronomical datasets, we will implement data and model driven machine learning techniques. Instead of predicting all the cross dependencies a priori, we will use deep neural networks to identify exoplanetary features in time-series (true Doppler signals, true transit signals) and on spectroscopic observations such as the ones that are being obtained from ground based and space based observatories. This project will work with both synthetic and real observations from ground and space based observatories. Detailed knowledge of machine learning is not required, but good coding skills (especially in Python, which is the main coding language for machine learning techniques) are strongly recommended.

In the last ten years, hundreds of exoplanets have been detected using blind surveys around nearby, bright, low-mass M-type stars with high-precision spectrographs like HIRES, HARPS, HARPS-N, or CARMENES.

The detection of such exoplanets always depended on a variety of parameters which have evolved and changed over this last decade: how are the radial velocities extracted from the observed spectra and which additional measurement can be implemented? Which corrections should be applied to the extracted time-series data? How does stellar magnetic activity phenomena such as dark spots, bright faculae, or granulation cells, affect the observed spectra? What can we know about the stellar activity of the host star, how can we extract that information, and which tool can be best used to mitigate those effects?

The advances we have made over the years in those questions, and our participation and exclusive data access to surveys such as HADES and CARMENES requests a revisiting of this approach using tools such as Exostriker or Juliet in order to find new, yet undetected exoplanets.

Compact stars, and more particularly neutron stars, are a unique laboratory for testing matter under extreme conditions. Over the past years a particular effort has been invested in studying different scenarios for the dense phases of matter in the core of neutron stars, from quarks to hadrons at high densities. The final aim is to understand neutron star observables, such as the mass, radius, magnetic fields or rotation, in terms of a plausible scenario for its interior.

For this purpose, theoretical approaches based on effective field theories for hadronic and quark matter have been developed in our group. The master thesis proposed aims at following the study of the interior of neutron stars by applying the previously developed theoretical frameworks to obtain the equation of state and transport properties of dense matter in the core of neutron stars. With these ingredients, we will be able to address the mass and radius of neutron stars as well as the dynamical properties of neutron stars, going from rotation to the effect of magnetic fields onto neutron stars.

Consistent theory of the universe evolution should include all known epochs from inflation to dark energy.
This maybe done effectively only within some modified gravity like F(R) gravity or Gauss-Bonnet gravity,etc., for review see S.Nojiri, S.D. Odintsov and V.K.Oikonomou,"Modified Gravity Theories on a Nutshell: Inflation, Bounce and Late-time Evolution," Phys. Rept. \textbf{692} (2017), 1-104 doi:10.1016/j.physrep.2017.06.001
The topic of current thesis will be precise realisation of this picture via the reconstruction of scale factor. This will require some theoretical knowledge and computational methods.

Type II core-collapse supernovae (SNe) are the tremendous explosions that mark the end of the lives of massive stars that retained a hydrogen-rich envelope until their death. Although most massive stars are born in close binary systems, where they are expected to exchange mass or even merge with a companion during their evolution, it remains challenging to determine which Type II SN progenitors experienced binary interaction prior to collapse. SNe in the local Universe provide a unique opportunity to investigate their evolution, as they can be studied with independent observational constraints, including properties of their host galaxies and direct progenitor detections in pre-SN images. Apparent discrepancies between the inferred properties of the progenitor star from these different methods can point toward a binary-interaction history. In this Master’s project, the student will focus on Type II SNe with empirical constraints from multiple sources, combining host-galaxy information from observations in the PMAS/PPak Integral-field Supernova Hosts Compilation (PISCO) with literature detections of progenitors from the Hubble Space Telescope, with the goal of identifying possible clues of binary interactions.

Since 2018, the Zwicky Transient Facility (ZTF) has discovered hundreds of thousands of supernovae and other optical transients, providing an unprecedented database of light curves with high cadence and long temporal coverage. This rich dataset opens the door to systematic searches for subtle features in supernova light curves that may reveal clues about their progenitor systems. In particular, small-scale undulations or bumps have been suggested as possible signatures of binary interactions prior to explosion, such as mass transfer or envelope instabilities. In this Master’s project, the student will collect and analyze all available ZTF transient light curves, applying statistical and visualization techniques to identify and characterize such deviations from smooth evolution. The ultimate goal is to assess whether these light-curve modulations can be linked to binary progenitor scenarios, thereby improving our understanding of the final stages of massive star evolution.

Type Ia supernovae (SNe Ia) and tidal disruption events (TDEs) are both luminous transients that can show similar colors and light-curve evolution during their early phases, making them difficult to distinguish without prompt follow-up. Since SNe Ia are the main contaminants in TDE searches, especially during the rising phase and in the absence of very blue photometry, systematic comparisons between the two classes are essential. In this Master’s project, the student will make use of public ZTF data to measure and document the rise times and rising colors (e.g., g–r) of SNe Ia and TDEs. The goal is to identify statistically significant differences between the populations that can serve as early-time diagnostics for TDE classification. Such results will provide valuable input for automated querying scripts and machine-learning classifiers, paving the way for rapid spectroscopic identification of TDEs in the upcoming LSST era. 

PhotSat is a project to follow-up the photometry of bright stars from space. It will consist of two telescopes of 10 cm aperture integrated in a cubesat that will monitor the full sky for 2 years. It will provide the photometry of stars from the UV to the optical wavelengths in three different broad-bands. These time series will be used to characterize the variability of stars and it will also be possible to detect transiting systems, either binary systems composed by stellar objects and brown dwarfs, or planetary systems.

In this project we aim to analyse the characteristics of the multiple systems that could be detected with PhotSat, based on the cadence of the observations and the performance of the instrument. The student will be in charge of producing realistic simulations of light curves for a diversity of binary and planetary systems, and devising the strategies to detect the transit signals.

Eclipsing binary systems are excellent laboratories to understand the structure and evolution of stars. The analysis of the photometric mutual eclipses and the radial velocity curves provides information about the size and the mass of the components. Besides, the monitoring of the times of eclipse allows to study the internal distribution of mass of the stars and also to infer the presence of additional bodies orbiting around the system, potentially planets.

The goal of this project is to seize the opportunity that precise photometry obtained from space, such as that coming from TESS, offers to improve the analysis techniques and to study different eclipsing binary stars, either to determine the properties of their components or to study their eclipse time evolution.

The recent detections of gravitational waves (GW) from merging binary black holes (BBHs) have opened a new window on the Universe. Yet, a fundamental question remains largely unanswered: where do these systems form and merge? Are BBHs the end products of massive stars in star-forming galaxies, or do they preferentially arise in globular clusters, galactic nuclei, or even in more exotic environments such as primordial black hole populations?

In this project, we will explore how to use large-scale structure as a tracer of BBH environments. By cross-correlating the sky distribution of BBH mergers detected by LIGO-Virgo-KAGRA and future GW instruments with galaxy surveys (e.g., DESI, Euclid, LSST), we aim to statistically infer the host halo masses and large-scale environments of these events. The student will:

• Learn about gravitational-wave astrophysics, large-scale structure, and galaxy clustering.
• Develop and apply cross-correlation techniques to simulated mock galaxy catalogues and real data at PIC (CosmoHub).
• Constrain models for the astrophysical origin of BBHs and primordial or relic BBHs.
  Assess the impact of this population on galaxy formation and clustering, connecting to upcoming survey data from Euclid and ARRAKIHS.

This project is well suited for students interested in cosmology, gravitational waves, and data analysis. It will involve both theoretical modelling and hands-on statistical methods, providing training that is highly relevant for future careers in astronomy and cosmology.

Traditional black hole models describe a one-way journey toward a singularity — a region where the laws of physics break down. Recent theoretical developments, however, suggest a radical alternative: a collapsing region inside a black hole could undergo a bounce, avoiding the singularity and re-expanding into a new universe. This scenario, known as the Black Hole Universe (BHU) model, replaces the classical Big Bang singularity with a Big Bounce emerging from the collapse of a finite overdensity in a larger “parent” universe and could be use to model our universe.

In this project, the student will investigate one of the most intriguing predictions of the BHU model: the formation of relic black holes during the collapse phase. These objects could contribute to the dark matter we observe today, potentially influencing the formation and evolution of galaxies. The student will:

• Develop a mass function model for relic black holes generated during the collapse.
• Explore their cosmological implications, including their possible role as dark matter and the relation to observed binary black holes.
• Assess the impact of this population on galaxy formation and clustering, connecting to upcoming survey data from Euclid and ARRAKIHS.

This project will combine theoretical modeling, cosmological simulations, and statistical analysis, providing a deep introduction to modern problems in cosmology and gravitational physics. It is ideal for students fascinated by early-universe physics, black holes, and the nature of dark matter.

The concordance model in cosmology, called LCDM, has been accurately reproducing the main cosmological observations for decades. However, the nature of its two main components, dark matter and dark energy as a cosmological constant, remains still unknown. Moreover, recent analyses start hinting at significant tensions compromising the ability of the model to explain our Universe. It is therefore of utmost importance to obtain even more accurate measurements to further test the standard model in cosmology. Galaxy surveys provide very useful data sets for cosmology and we are currently starting the golden era of stage-IV galaxy surveys. The Dark Energy Spectroscopic Instrument has already been operating for a few years. The first data release of the Euclid mission is expected by mid 2027, the Rubin observatory started observations last June, and the Nancy Grace Roman space telescope was just launched last August. These four galaxy surveys are very complementary. Each one has their own scientific goals and particularities, like depth, angular coverage, or resolution. The goal of this project is to produce realistic forecasts not for one of these surveys but for the four of them. And then to forecast the constraining power of a combined analysis to fully exploit the synergies between the different surveys. Such a combined analysis from galaxy survey data, together with additional cosmological probes, such as type-Ia supernovae or the cosmic microwave background, will provide very tight constraints on the cosmological parameters that will eventually allow us to shed some light into the dark sectors of the Universe.

Massive stars are powerful cosmic engines, driving the cycle of matter in galaxies. Their strong winds and intense radiation carve vast bubbles into the surrounding gas, creating circumstellar nebulae that evolve with the star’s life. The size and shape of these bubbles depend both on the star’s winds and on the conditions of the environment around them. As the star changes, its bubble reflects those evolutionary stages, and, ultimately, sets the stage for the star’s explosive death as a supernova.

When the star finally explodes, the expanding remnant may contain a rapidly spinning neutron star, or pulsar. This pulsar can unleash a stream of high-energy particles, creating a pulsar wind nebula, like the famous Crab Nebula. To understand these spectacular nebulae, we must first understand the physical properties of the parent bubbles in which they are born.

The Multi-Messenger Astrophysics (MAP) group is at the forefront of exploring how the life and death of massive stars shape their surroundings. This project invites a Master’s student to join this effort, using advanced hydrodynamical simulations with the state-of-the-art PLUTO code to study the growth and evolution of stellar wind bubbles. In particular, we will together investigate how a star’s metallicity, its chemical make-up, affects the formation of these bubbles. This will, for the first time, provide a time-dependent view of how massive stars sculpt their environments in different galaxies, including the Milky Way, the Magellanic Clouds, and the extremely metal-poor Zwicky 18.

By studying these cosmic structures, you will help reveal how massive stars prepare the very cavities that will later host pulsars, unlocking new insights into the most powerful life cycles in the universe. 

Cosmological simulations are key ingredients to prepare and exploit the new generation of galaxy surveys. Typically, large supercomputing resources are required to develop high-fidelity simulations that can accurately mimic the large-scale galaxy distribution we observe. As the quality of the new observational data improves, the level of detail reproduced by numerical simulations already demands prohibitive computational resources.  Alternatively, clever ways of modeling the evolution of the large-scale structures in the universe have been proposed to achieve promising results at a much lower cost.  

We propose to explore new methods, based on Machine Learning techniques, to model both the large and small scales of the so-called “cosmic web”, allowing for a fast and efficient way to optimally exploit the new generation of cosmological surveys that promise to unveil the nature of dark-matter and dark-energy in the universe.

Gravitational Wave Astronomy began in 2015 with the first detection by the LIGO observatory of the gravitational wave emission produced by the collision of two black holes (Nobel Prize in Physics 2017). To be able to detect gravitational waves from binary systems of supermassive black holes (millions of times the mass of the Sun) we need to go to space. The European Space Agency is leading the LISA mission that will be launched in 2035 and has just entered the implementation phase. To be able to detect these systems, precise gravitational emission waveforms and efficient data processing algorithms are needed.

The aim of this project is to consider "simple" models of gravitational wave emission from binary systems of supermassive black holes when they are close to the collision phase and to design efficient algorithms for searching for these signals in synthetic data. In particular, these models must support the use of automatic differentiation for efficient calculation of gradients, so that they can be used with Bayesian inference methods that use these gradients, such as Hamiltonian Monte Carlo methods. In this sense, it is also important to incorporate the response of the LISA observatory in an efficient way.

The project will consist in the following tasks: (1) Optimization of some gravitational waveform generation models for binary black hole systems and verify that the application of automatic differentiation is efficient and gives reliable results. (2) Adapt the LISA response for these gravitational wave models in such a way that the use of automatic differentiation is possible. (3) Study the methods of sampling by Bayesian inference,  in particular the Hamiltonian Monte Carlo method. (4) Apply these methods, using open sources, and study the efficiency of models that allow the use of automatic differentiation in comparison with traditional models.

X-ray binaries (XRBs) are systems in which a compact object accretes material from a low-mass companion star. These binaries exhibit complex (and often dramatic) variability in their X-ray emission. Their behavior provides key insights into the physics of accretion, the launching of jets and outflows, and the interaction between compact objects and their environment under extreme physical conditions. 

With the recent launch of the Einstein Probe satellite, we are entering a new era in the study of XRBs. Thanks to its wide field of view and high sensitivity, Einstein Probe enables regular monitoring of both newly detected and well-known systems across the Galaxy, capturing their temporal evolution with unprecedented detail.

In this project, you will work with Einstein Probe data to investigate the variability properties of selected XRBs, characterizing their flux changes and interpreting the results within the broader framework of variability and accretion processes in XRBs.

In Astrophysics, the study and characterization of chemistry is commonly related to the search for (new) molecular species in astronomical environments and to the characterization of their properties (e.g., molecular abundance, temperature, spatial distribution, kinematics of the gas associated with them). Based on this, Astrochemistry has two major goals: (1) to use chemical species and their properties to derive key (physical) knowledge of the sources themselves (e.g., their mass, their temperature, their dynamic stage), and (2) to understand how chemistry evolves in time, increasing in complexity until eventually resulting in the formation of (pre-)biotic molecular compounds.

The goal of this project is to use state-of-the-art astronomical observations (with e.g., ALMA) to characterize and understand star-forming regions. For this, we use spectral line observations that allow us to determine the physical status of dense cores and clouds where the new generations of stars and planets form. Moreover, by studying the chemical composition of different objects we can search for evolution in the chemical content. Finally, observations of different objects throughout the Galaxy enables the search for chemical differences in the inner and outer regions of the Galaxy.

Most stars do not form in isolation, but in rich clusters containing hundreds of stars that are initially deeply embedded inside large molecular clouds. Therefore, understanding the formation of stars, and eventually planets, requires characterising the fragmentation process of the molecular cloud into dense cores out of which stars will eventually form. The number of newly-formed stars with a given mass, the so-called IMF (initial mass function), is a key parameter in the study of the formation and evolution of clusters that transcends all astrophysical fields. During the last decades, some theories have claimed that the IMF is related to the masses of the dense cores that fragment out of the molecular cloud, the so-called CMF (core mass function). The first observational results supported this possible connection, however biases and limitations on the spatial resolution and the accuracy of core mass determination may have affected the results obtained so far.

We seek to overcome these known observational biases and perform a detailed study of the CMF in four embedded clusters at different evolutionary stages, emerging from the same molecular cloud. For this, we have acquired ALMA band 6 (220 GHz) observations, reaching a spatial resolution of 200 au and a mass sensitivity of 0.1 Msun, which will allow us to resolve all the members in the cluster and probe the CMF from low to high core masses. The student will work with new high-quality ALMA data to produce images of the dust continuum emission of the dense cores in these four clusters. Following the generation of the astrophysical images, the student will use automatic procedures to identify and extract all the detected cores. This will allow us to determine properties such as their masses, sizes and location within the cluster. With the masses, the CMF of these clusters will be constructed and compared to the IMF.

Since the first detection of gravitational waves in 2015, gravitational wave astronomy has been transforming fundamental physics and astrophysics.

In order to decode the observed gravitational wave signals and identify their sources (e.g. to determine the nature of the compact objects as black holes or neutron stars, or measure their masses and other properties), one needs to compare theoretical models of the waveforms with the observational data using the methods of Bayesian statistical analysis.

The scientific insight that one can gain from the signals is thus not only limited by the  sensitivity of the detectors, but also the accuracy of our waveform models. Such models are synthesised from information obtained from  different perturbative approaches to solve the Einstein equations, and from large scale numerical simulations of compact binaries in general relativity.

The aim of the project will be to improve waveform models developed within the phenomenological waveforms approach, which has produced several families of computationally efficient codes that have been used by the LIGO-Virgo collaboration to analyse all gravitational wave events detected to date. Together with the student a suitable building block of the next generation of waveform models will be selected, which could focus on aspects such as high mass ratios, the effects of spin precession, or orbital eccentricity. From a technical point of view, the project could either focus on modelling simulation data, to carry out simulations, or on the development of efficient code implementations, e.g. using GPUs.

Stellar wind bubbles are the circumstellar nebulae forming around massive stars when their
supersonically-expanding feedback interacts with the interstellar medium of galaxies. Their formation
and evolution is mainly governed by the stellar wind properties and by the local conditions of the
ambient medium (Weaver et al. 1977, Wilkin et al. 1996). Throughout the star’s life, they reflect their
central star’s evolutionary phase and they shape the environment where high-mass stellar objects will
die by exploding as a supernova. This generates a supernova remnant, inside of which a strongly
rotating magnetised neutron star, or pulsar, might form and release its relativistic wind, giving birth to a
pulsar wind nebula. Hence, the understanding of pulsar wind nebulae requires first a comprehension of their parent environment (Meyer & Meliani).

Such environments can only be probed by numerical simulations. This Master’s project aims at
investigating the formation of circumstellar nebula around massive stars. It will, by means of 1D
hydrodynamical simulations, study the evolution of stellar wind bubbles of high-mass stars using the
in-house setups for the PLUTO code (Mignone et al. 2012). We will explore the effects of the
metallicity onto the formation and evolution on these stellar environments, obtaining thus a time-
dependent picture of how massive stars shape their surroundings, e.g. in the small and large Magellanic
clouds, and we will pronounce on the properties of the cavity that will later host young pulsars.

Stellar activity poses a major limitation to the extraction of planetary signals from radial velocities and transits. An evolving and rotating inhomogeneous star surface hampers the detection of small planets in temperate orbits and also atmospheric characterization of exoplanets using transit spectroscopy. Our ability to account for these effects is closely related to improving our understanding of stellar activity as a function of time and wavelength. This project will develop methodology to retrieve planetary signals from data affected by activity. One of the main tools will be the StarSim code, which is capable of accurately simulating stellar variability effects. Among other sources, proprietary data from the CARMENES radial velocity spectrometer will be analyzed.

The SPMN-CSIC network records about 20,000 meteors and fireballs every year, occurred over continental and insular Spain and neighboring countries. These luminous phenomena are produced by the arrival at hypervelocity of asteroidal and cometary rocks suffering ablation, and creating an ionized column called meteor. All these recordings are stored into the SPMN-CSIC meteor and fireball database that has been operational for 27 years. The goal of the proposed TFM is providing the candidate the basic skills to complete the astrometric measurements using a well-tested routine, and to learn the full reduction process of these data for obtaining valuable scientific publications. Then, using meteor recordings from several CCD and video stations all over Spain and Catalonia, we will be able to reconstruct the atmospheric trajectories, to obtain the radiant and incoming velocity, and finally to infer the heliocentric orbit in the Solar System of the meteoroids producing the recorded meteor events.

I envision a practical TFM, teaching the right methodology, defining several case studies and establishing a publishing goal to be achieved. All together to provide an appropriated student training, by gaining the required skills to continue a PhD thesis on this subject.

Requirements: A significant knowledge of English and Python are needed to be considered.

Hot Jupiters are giant planets orbiting extremely close to their host stars, which irradiate them to temperature of a few thousands of kelvin, and tidally lock their rotation to their orbital period. Their unique environment, not present in our solar system, set them as a peculiar astrophysical laboratory: their climate is heavily affected by the thermal winds which try to redistribute through the planets the excess heat from dayside, equatorial regions; their origin calls from efficient migration from outer disk at early times; their size and mass make them the easiest targets for observational detection and characterization. A puzzling feature is that they systematically show a radius up to twice the value one would expect for such planets. A continuous heating mechanism is believed to be responsible for the extra heat they need to keep themselves internally hot and puffy. Ohmic dissipation model, consisting on the resistive dissipation of atmospherically induced electrical currents, is the most quantitative and promising scenario to explain hot Jupiter inflation. Crucially, such model is tightly related to the existence of a dynamo, and to the non-trivial climate, which is affected by magnetic fields. In the project, the student will use and adapt an existing, public evolutionary code, successfully used in the recent years by the group, to explain properties of the observed population, aiming at a specific, well-characterized sample, in order to infer their internal properties.

The Cosmology and Extragalactic Astronomy groups at ICE-IFAE-PIC have a long expertise on generating mock galaxy catalogs for several large extra-galactic surveys ongoing or being in which we actively collaborate such as PAU, DES or Euclid. In order to fully exploit and interpret the observed data from galaxy surveys it is essential to produce mock galaxy catalogues since they can help in a variety of ways. They are useful to design and calibrate galaxy surveys. They can help to study selection effects, to calibrate errors and explore systematic effects, to test new techniques to measure cosmological parameters or to calibrate cluster finders and photometric redshift estimators.

Accurately reproducing observed distributions in simulations is mandatory to achieve successful scientific analysis. In this Master thesis project we propose to apply in a novel way a method to estimate a continuous transformation that maps one N-dimensional probability density function distribution to another. This method will allow not only to reproduce the observed distributions but also to maintain the correlations between the observables. We will apply and validate this methodology using MICE and/or Euclid simulations.

Protostars are the progenitors of stars. They are star forming objects that intensively accrete mass from their immediate environment, more precisely from the circumstellar disk and the infalling envelope. Studying them thus allows us to understand how do stars acquire their fundamental properties of mass, angular momentum, and magnetic field. The protoplanetary disk (the future planet hosting disk) also forms during the protostellar phase, meaning that studying the evolutionary processes at play in these systems is crucial for our understanding or both star and planet formation.

The accretion of mass onto the central protostellar is accompanied by the launch of high velocity (~100-200 km/s) jets, carrying mass (~10^-7 to 10^-9 solar mass per year) and angular momentum form the central regions. The goal of this project is to study the jet launched by a prototypical young protostar located in the Serpens star forming cloud, with the synergy of deep ALMA high-angular resolution and recent JWST spectroscopic observations. Both ALMA and JWST data present very complementary emission spectral lines of the shocked structures propagating within the jet. ALMA data offers high spectral resolution lines that will characterize the dynamic of the jet (velocity, structures, evolution), and the JWST data spans several shock tracers (H2, FeII) and ionization tracers (NeII, ArII, SI) that will allow to study the excitation and chemical content of the gaz.

The student will start by reducing and imaging the ALMA and JWST spectroscopic observational data, then study the velocity/amplitude/structure of the emission lines seen in both datasets. Secondly, modeling of these emission lines will be performed to constraint the physical parameters (chemical content, velocity, irradiation, density, magnetic field) and dynamics (structures, evolution) of the shocks. This work will involve the use of pipeline reduction scripts (ALMA and JWST pipeline in python), of data analysis scripts (looking at spectral data cube in python), and of physico-chemical models (in batch and python).

The conjonction between these two cutting-edge datasets is unprecedented and will provide for the first time a compete view of the shock internal structures within a protostellar jet, which in turn will improve our understanding of the physical mechanisms launching these jets, and how do they impact the surrounding interstellar medium. 

Hydrogen-rich supernovae (SNe) showing long-lasting narrow emission lines in their spectra are known as SNe IIn. These objects arise from massive stars undergoing core collapse within a dense hydrogen-rich circumstellar medium (CSM). The source of the narrow emission lines is believed to be the result of interaction between the SN ejecta and this CSM, related to progenitor mass–loss episodes before the explosion. The physical mechanisms driving the mass loss are still not well understood. However, the environments where SNe explode can provide helpful information about these mechanisms and their progenitors. Therefore, this project aims to explore the environments of SNe IIn to constrain the progenitor properties of these interacting SNe and the role of metallicity in mass loss. The student will work with observations (data from the literature), astronomical tools, and Python codes.

Hydrogen-rich supernovae (SNe II) are produced by the final explosion of massive stars (>8 Msun). They retain a significant fraction of hydrogen at the moment of the explosion, and hence their spectra show prominent Balmer lines. Recently, SNe II have been proposed as metallicity indicators, making them relevant in the cosmic context. More precisely, theoretical models predict that the strength of metal lines around 50 days post-explosion is related to the metallicity of the SN progenitor [1]. Thus, SN II metal-line pseudo-equivalent-widths (pEWs) generally become stronger when metallicity increases. This project aims to explore this correlation and test the parameter space obtained from the models. The student will work with observations and models, astronomical tools and python codes. The sample used for the project comprises spectra from the literature and new observations, plus theoretical models developed by Dr Luc Dessart.