Application Instructions

The call for 2027 is open! Apply by 4 p.m. PDT Tuesday, March 31, 2026.

Eligible applicants must fulfill all of the following requirements: 

• Hold United States citizenship, national, or permanent resident status by the application deadline. Applicants may currently be enrolled at US or non-US institutions.
• Currently enrolled in a PhD program in Astronomy or Physics.
• Should have completed all classwork for a graduate program degree by December of the year the application is submitted.
• Be available to spend 6 months at IPAC, from February to August.

Each applicant must submit:

• A brief (~2 page) letter of introduction that includes:
  • Your current status as a graduate student and expected completion date. The optimal timing for this fellowship is after the student has completed their coursework, but before the final semester of their thesis, when it is expected that they are concentrating on their dissertation and not able to completely switch focus to a new project. Please address the timing of this fellowship and how it fits into your thesis plans.
  • Description of your past research experience and current research interests.
  • Please rank your top three IPAC research project choices and include your reasons for how they match your research interests. The ideal project is one that extends your work in a natural way; for instance, a new dataset to which you can apply tools you are already familiar with, or learning to apply new tools to a dataset you are already familiar with. Given the relatively short (6-month) nature of the fellowship, the best case scenario is for students to be able to hit the ground running!
• A one-page CV that includes experience you may have with astronomical and image processing software packages (e.g., Python, IDL, HIPE, AIPS, etc.)

Apply Now

In addition, we ask that a current professor or academic advisor familiar with the applicant’s work upload a letter of reference (PDF) using this page. This letter should also indicate that the applicant is available to visit IPAC during the proposed period, and address both how well the visit would mesh with the applicant’s graduate education, and how the timing of the fellowship fits into the students' thesis plans.

Submit Letter

Questions? Please contact the program coordinator, Dr. Jessie Christiansen, christia [at] ipac.caltech.edu

2027 Research Projects

Unveiling Galaxy Ionizing Power with JWST Slitless Spectroscopy

Advisor: Anahita Alavi

The Parallel Application of Slitless Spectroscopy to Analyze Galaxy Evolution (PASSAGE) program is a landmark JWST survey designed to transform our understanding of galaxy evolution. Operating in Pure Parallel mode, PASSAGE observed 63 high-latitude fields and received the largest allocation of JWST observing time in Cycle 1, 591 hours of NIRISS near-infrared imaging and slitless spectroscopy. This unprecedented dataset enables an unbiased spectroscopic view of faint galaxies, without prior photometric pre-selection.

Despite recent progress, fundamental questions remain: How efficiently do galaxies produce ionizing photons (ξₒᵢₙ)? This quantity is critical for understanding the role of galaxies in cosmic reionization yet remains highly uncertain. Notably, 15 PASSAGE fields overlap the COSMOS footprint, allowing PASSAGE spectroscopy to be combined with available ultraviolet imaging both from HST and ground. This synergy enables direct measurements of ξₒᵢₙ at cosmic noon (z ≈ 1–2), the peak epoch of star formation in the universe.

This project offers graduate students a unique opportunity to work hands-on with cutting-edge JWST data, collaborate with the PASSAGE team and access to the PASSAGE grism-slitless NIRISS data, catalogs and software.

Galaxy Structural Evolution in the Cosmic Web with Lyman-alpha Tomography 

Advisor: Nima Chartab

The role of large-scale environment in regulating galaxy growth is well established at low redshift but poorly constrained during the epoch of peak cosmic star formation at 2 < z < 3. A central obstacle has been the difficulty of mapping the density field at these redshifts without relying on galaxy overdensities, which can be biased toward the galaxy population being observed. This project addresses that limitation by leveraging the Lyman-alpha Tomography IMACS Survey (LATIS), which has provided the largest Mpc-resolution three-dimensional map of the intergalactic medium at z~2.5 to date by observing the Ly-alpha forest in the spectra of thousands of background galaxies. This method yields a galaxy-independent measure of large-scale environment, mitigating the selection biases of galaxy-based tracers. Combined with deep JWST/NIRCam imaging from the COSMOS-Web survey, which resolves galaxy structure in the rest-frame optical across the same field, this enables a direct test of whether large-scale environment shapes galaxy structural evolution at cosmic noon.

The student will correlate structural and morphological measurements from JWST imaging, including indicators of compactness and interaction signatures, with the LATIS maps to test whether structural transformation and merger activity are enhanced in protoclusters and/or filaments. Deep learning models will be developed and applied to classify galaxy morphologies and interaction states in a scalable manner.

This project will produce a direct measurement of environment-dependent galaxy structural evolution at z~2.5 using a selection-independent large-scale structure map, offering new constraints on mechanisms such as enhanced merging and early quenching during the universe's most active epoch, with results expected to lead to a publication.

Using Machine Learning to Generate the Palomar Spectroscopic Survey of Young Stars

Advisors: Jessie Christiansen and Kevin Hardegree-Ullman

There are an increasing number of exoplanet demographics studies that rely on stellar ages, with the goal of mapping out how planets form, migrate, and evolve with time (e.g., Christiansen et al. 2023; Vach et al. 2024). However, for young stars, there are few catalogs of stellar parameters of the size and uniformity needed for robust demographics analyses. Over two semesters we acquired spectra of >200 young FGK stars with DoubleSpec (an optical spectrograph on the 5-m Hale Telescope at Palomar) and 25 young M dwarfs with TripleSpec (a near-infrared spectrograph on the same telescope). Our goal is to use these spectra as a machine-learning training set and ultimately build a large, uniform, well understood atlas of young star parameters.

A visiting graduate student would reduce the spectra, derive stellar properties, and ultimately use these to build the machine-learning training set for the much larger sample of young stars observed by Kepler, K2, and TESS. The student would also be encouraged to come up with a better acronym or name for the final atlas.

Toward eta_Earth: Building a Framework to Combine Kepler and Roman exoplanet demographics

Advisors: Jessie Christiansen

NASA's next flagship mission, the Nancy Grace Roman space telescope, has as a baseline science requirement to measure the frequency of Earth-sized planets. The Roman data themselves should constrain planets from 1-10au, which is very complementary to the Kepler data, which have well constrained planets interior of 1au. The true power of the data from the two missions will be in their combination, to provide a complete, self-consistent of planetary systems out to 10au. However there are challenges to combining data from these two datasets, not least of which is that the stellar populations the two missions are probing - Kepler nearby solar-type stars, and Roman distant FGKM stars toward the Galactic center.

The visiting student would work to understand the differences in the populations, their impacts on the expected exoplanet populations, and build a framework to combine surveys across the two stellar populations. The framework would be tested with real and simulated data, and could be later used to provide predictions for how Roman data could be used to discriminate between different effects of stellar populations on planet demographics.

Extreme Galaxies in the Census of the Local Universe (CLU) Survey

Advisor: David Cook

The Census of the Local Universe (CLU) is a large-area survey that aims to find new galaxies in the local Universe out to a distance of 200 Mpc (z~0.05). We utilize four narrow-band filters to search for H-alpha emission-line sources across 26,000 deg^2 of the sky; similar in footprint to Pan-STARRS. The new galaxies found in this survey will be used to search for counterparts to Gravitational Wave events and enable the discovery of extreme galaxies (BCDs, metal-poor galaxies, green peas, etc.) that are rare in the local Universe. The source catalogs for the entire survey have recently been published, and are ripe for data mining galaxies with extreme emission-line properties.  We anticipate discovering several thousand new BCDs and green peas during this project. 

We are seeking a student to develop and implement methodologies to separate extreme galaxy candidates from normal star-forming galaxies and nebular regions in the Milky Way. The resulting candidates can then be combined with data from other large surveys to derive physical properties (stellar mass, star formation rate, metallicities, etc.) to enable studies of galaxy evolution and star formation.

We seek a student with a background in galaxy evolution, star formation, or analysis of large data sets to discover thousands of exciting and rare objects. 

Investigating the Requirements for the Detection of Filaments with Weak Gravitational Lensing

Advisor: Kyle Finner

Cosmological simulations have shown that the universe is comprised of a cosmic web of dark matter filaments. At the nodes of the filaments are galaxy clusters that have been well-studied with weak gravitational lensing. The next frontier in weak lensing will be to probe to lower density contrasts and map out the filaments that connect the clusters. Ongoing and upcoming imaging surveys, such as Euclid and Roman, are providing our deepest, wide-field view into the universe and combined with advances in weak-lensing techniques will enable the study of filaments.

The student will utilize cosmological simulations, such as Illustris TNG, to investigate the weak-lensing catalog and techniques that are needed to significantly detect large-scale filaments. Properties of imaging such as galaxy number density and accuracy of redshift as well as techniques such as galaxy shape fitting and mass mapping will be studied to form a clear picture of the requirements to map out filaments. The student will then apply their techniques to the latest Euclid observations and forecast what will be possible with the Roman telescope.

Distentangling Exoplanet Atmospheres and Stellar Activity with Pandora

Advisors: Emily Gilbert and Aurora Kesseli

Pandora is a NASA Pioneers mission that launched in January 2026 with the goal of disentangling stellar activity from exoplanet signals to more accurately constrain exoplanet atmosphere transmission spectra. Pandora utilizes simultaneous optical photometry with near-infrared spectroscopy in order to characterize exoplanets and their hosts stars. Pandora is specifically targeting low mass stars with varying activity levels.

We invite a student to work with Drs. Gilbert and Kesseli, in collaboration with the Pandora science team, to reduce and analyze data from this groundbreaking mission. We anticipate the student will lead the analysis of a Pandora exoplanet target. The student would work to characterize host star, placing constraints on spot coverage fractions. Using this information, they will also obtain reliable constraints on atmospheric parameters which are free from stellar contamination using common techniques such as retrievals. This project has the possibility to include additional datasets (e.g. TESS, LCO, Keck), if desired.

Foundation Models for Euclid Science

Advisor: Shoubaneh Hemmati

Euclid is delivering multi-band imaging of billions of galaxies, opening unprecedented opportunities and challenges for extracting scientific information at scale. Recent astronomical foundation models, such as AstroPT, have already demonstrated promising zero-shot performance on Euclid data, raising important questions about when additional fine-tuning is beneficial and when it offers diminishing returns. This project focuses on systematically quantifying the gains from different levels of model adaptation, from zero-shot inference to lightweight fine-tuning, across selected Euclid science tasks. The student will benchmark performance, data requirements, and computational cost, and explore how learned representations can be reused for discovery problems such as identifying rare or unusual objects. The goal is to establish practical guidance for using foundation models efficiently and robustly in the Euclid, Roman, and Rubin era.

Cross-Survey Transfer Learning for Galaxy Population Studies

Advisor: Shoubaneh Hemmati

Understanding galaxy evolution requires comparing galaxy populations across surveys that differ in depth, resolution, and wavelength coverage, yet most machine-learning classifiers are trained independently for each dataset. This project investigates how models trained on one survey can be transferred to others with minimal additional labeling, enabling more consistent population studies across HST, JWST, Rubin, Euclid and related datasets. The student will explore transfer learning and domain adaptation strategies on matched samples, quantify how much labeled data is needed for reliable generalization, and assess where survey-specific models break down. The goal is to develop practical, scalable approaches that allow galaxy populations to be compared more uniformly across cosmic time.

Representation Learning for AGN Variability and Transitions

Advisor: Shoubaneh Hemmati

Active galactic nuclei exhibit complex, multi-wavelength variability that encodes information about accretion physics and black hole growth, but this structure is difficult to capture with hand-designed features. In this project, the student will develop self-supervised representation learning methods (e.g., JEPA-style architectures) to model AGN variability directly from irregular, multi-band light curves, learning latent representations that summarize both long-term trends and short-term fluctuations across wavelengths. These representations can then be used to study AGN populations and to search for signatures that precede dramatic variability events such as changing-look transitions. The project bridges time-domain astronomy and modern deep learning, with an emphasis on extracting physically meaningful structure from data-driven models.

Breaking the Duty-Cycle Degeneracy in AGN Evolution

Advisor: Shoubaneh Hemmati

Current models of early black hole growth face a fundamental degeneracy between black hole–galaxy scaling relations and AGN duty cycles, limiting what can be inferred from high-redshift observations alone. This project uses complementary datasets from JWST, Euclid, and low-redshift AGN variability studies to trace how AGN duty cycles evolve from cosmic dawn to the present. The student will combine number-density measurements and variability-based constraints to test competing evolutionary scenarios and assess where existing models succeed or fail. By leveraging Euclid’s wide-area coverage at intermediate redshifts, the project aims to connect early black hole growth to the well-studied local universe in a unified, empirical framework.>

The Disappearance of PAHs in Dwarf Galaxies with JWST

Advisor: Thomas Lai

Polycyclic aromatic hydrocarbons (PAHs) are key tracers of star formation and the dust–gas cycle in galaxies, yet their abundance drops sharply in low-metallicity environments. This project will investigate why and how PAHs disappear in blue compact dwarf galaxies (BCDs) — local analogs to the metal-poor, high-redshift galaxies that dominated the early universe — offering a rare window into dust evolution across cosmic time. The student will collaborate with Dr. Lai to analyze JWST NIRSpec IFU spectroscopy of a sample of BCDs spanning a wide metallicity range, targeting the critical 3.3 μm PAH feature to probe the survival of the smallest PAH grains, complemented by available MIRI IFU spectroscopy to broaden spectral coverage and probing PAH features at longer wavelengths. Through this project, the student will develop expertise in JWST NIRSpec and MIRI IFU data reduction and spectral decomposition, building the skills to identify and interpret trends in dust properties across a diverse galaxy sample and address open questions about PAH survival in the early universe.

Linking the UV bump with Dust Grain Properties in Blue Compact Dwarf II Zw 40 with Hubble and JWST

Advisor: Thomas Lai

The 2175 Å UV bump was first detected in the 1960s, yet its exact origin remains uncertain. This project will investigate the nature of the UV bump and its possible connection to polycyclic aromatic hydrocarbons (PAHs) in the blue compact dwarf galaxy II Zw 40. Despite its low metallicity, dust emission has been detected in II Zw 40, making it a valuable local analog for high-redshift galaxies and providing key insights into dust evolution and star formation in extreme environments. The student will collaborate with Dr. Lai to analyze deep HST UV observations, constraining the UV bump and mapping star clusters. These data will be complemented by JWST NIRSpec and MIRI IFU spectroscopy to investigate PAH emission, dust properties, and molecular gas. Through this project, the student will gain experience in multi-wavelength data analysis spanning from the UV to the mid-infrared, including HST image processing, star cluster identification, and JWST spectral fitting, contributing to a deeper understanding of dust composition and star formation in low-metallicity galaxies.

Dust and Diffuse Emission Mapping with SPHEREx

Advisor: Wanggi Lim

We propose a research project focused on constructing and utilizing a spectrally resolved model of the diffuse Galactic background emission using the full 102-channel spectral imaging data from the SPHEREx mission, covering 0.75–5.0 μm at moderate spectral resolution. The visiting graduate fellow will work with newly available SPHEREx data products to analyze diffuse emission and extinction properties across the inner Galactic plane, enabling extinction mapping and spectral characterization of dust in regions where traditional stellar-based methods are limited.

The SPHEREx Year 1 data release, scheduled for November this year, will provide full-sky spectral data cubes in all 102 channels. By the time the graduate fellow joins in early 2027, these datasets will be fully accessible, allowing the student to directly utilize unprecedented spectrally continuous observations of the diffuse interstellar medium. The fellow will participate in constructing background and extinction maps, evaluating uncertainties through cross-validation, and investigating spatial variations in dust properties and diffuse emission.

This project will provide hands-on training in analyzing large-scale spectral imaging datasets, diffuse emission modeling, and multi-wavelength ISM diagnostics. The resulting products and analysis will contribute to community-use calibration and foreground characterization for major facilities such as JWST and the Nancy Grace Roman Space Telescope, while providing the fellow with practical experience in modern observational astrophysics and survey-scale data analysis.

Hunting Dust Properties of Extreme Star-Forming Regions

Advisors: Wanggi Lim and Sean Carey

Understanding the dust properties in extreme star-forming regions is essential for constraining the initial conditions of star and planet formation. Dust plays a fundamental role in the interstellar medium (ISM) by regulating gas cooling, providing sites for molecule formation, and influencing radiative transfer. In particular, infrared dark clouds (IRDCs) are key sites of early-stage star formation, characterized by their dense, cold, and high-extinction environments. Despite their importance, the detailed dust properties of IRDCs, especially in extreme star-forming conditions, remain poorly constrained.

This study aims to characterize the dust properties of an IRDC in the Milky Way by analyzing its absorption and emission from the mid-infrared (MIR) to the millimeter regime. Specifically, we will employ MIR and far-infrared (FIR) extinction maps, gray body-fitted temperature/density maps, and spectral index (β) derivation to investigate how dust properties vary with environmental conditions. By comparing dust properties with local physical parameters such as temperature, density, and radiation field strength, we seek to understand the role of dust evolution in shaping star-forming environments and its potential effect on star formation activity.

The analysis will be based on a combination of archival data from Spitzer, WISE, and Herschel, along with ALMA data available to the team. These multi-wavelength observations will allow us to trace dust properties across a wide range of conditions, providing critical constraints on how dust evolves from the diffuse ISM into the dense cores where stars and planets form. The results of this study will contribute to a broader understanding of the interplay between dust evolution and the physical conditions that govern star formation, ultimately informing models of planet formation by constraining the initial conditions under which protoplanetary material originates.

This project is well suited for students interested in observational studies of the ISM, dust evolution, and star formation. While prior experience with dust modeling, extinction mapping, or radiative transfer is beneficial, it is not required. Enthusiasm for learning and analyzing multi-wavelength astronomical datasets is the most important qualification.

Deriving a Dust Extinction Map of the Galactic Plane from SPHEREx Hydrogen Recombination Lines Data

Advisor: Roberta Paladini

The SPHEREx (Spectro-Photometer for the History of the Universe, Epoch of Reionization and Ices Explorer) mission launched on March 11^th, 2025. The mission is currently observing the full sky in 102 spectral bands from 0.75 to 5 micron with a 6.15" angular resolution. In this NIR wavelength range, several hydrogen recombination lines are found. The proposed project—by comparing the observed vs. predicted intensity of these lines—aims at constructing a dust extinction map for the entire Galactic Plane, following the remarkable work described in Fritz et al. (2011).

Probing Galaxy Evolution with Emission Line Galaxies Through JWST/NIRISS Grism Spectroscopy 

Advisors: Vihang Mehta, Kalina Nedkova, Zahra Sattari

JWST slitless spectroscopy is transforming how we study galaxy evolution across cosmic time by opening an unprecedented window onto the low-mass regime, the key frontier for understanding how galaxies assemble their stars and study their interstellar medium. JWST has now obtained nearly 800 hours of NIRISS grism observations across hundreds of independent fields, spanning 1-2.3 μm and covering up to ~400 sq. arcmin. These programs deliver a powerful, unbiased spatially resolved spectroscopic dataset for thousands of galaxies across z ≈ 1-3.5. The wavelength coverage includes major optical emission lines, such as Balmer lines, [O III], and [O II], enabling detailed measurements of stellar populations and nebular physics across a wide range of environments and cosmic epochs. This rich dataset supports a broad range of science: tracking the evolution of galaxy physical properties over time, performing spatially resolved studies of metallicity and ionization structure, probing galaxies during the epoch of reionization, and uncovering rare and extreme systems.

We invite PhD students to join this effort and explore how galaxies grow and evolve using this unique JWST grism dataset. Students will work with the reduced JWST data and can pursue projects focused on stellar and nebular modelling, resolved galaxy physics, emission-line diagnostics, or other original directions enabled by these observations. The project offers opportunities to develop expertise in cutting-edge data analysis, physical modelling, and JWST science within a collaborative and supportive research environment.

Revealing the Evolution of Dust Attenuation in Star-Forming Galaxies with Keck + JWST

Advisors: Vihang Mehta, Kalina Nedkova, Zahra Sattari

Dust is one of the most important components in how light is processed within galaxies and, in turn, it strongly affects the inference of galaxy properties. A robust description of dust attenuation curves and how they evolve is thus a critical ingredient in modelling galaxy spectral energy distributions as dust can introduce significant systematics on derived stellar masses and star-formation rates. This directly limits the accuracy and precision to which theories of galaxy evolution can be refined and are critical for upcoming surveys with Rubin, Euclid, and Roman.

Imaging campaigns with Keck/LRIS are now providing the necessary photometric coverage in the rest-frame optical and ultraviolet wavelengths required to study dust attenuation across a wider range of galaxy properties and cosmic time than previously possible. We invite a PhD student to combine 4-band imaging from recent Keck/LRIS observations with JWST deep grism spectroscopy and imaging data to derive dust attenuation curves using hundreds of star-forming galaxies. This is expected to provide fundamental insight into how dust properties and dust attenuation curves vary between galaxies and which intrinsic galaxy properties (e.g., stellar mass, inclination) drive attenuation variation. This will help to inform more versatile prescriptions of dust attenuation as a function of cosmic time and provide numerous opportunities to study integrated properties of star-forming galaxies at intermediate and high redshifts.

Clumpy Galaxies in Transition: A Euclid View of Evolving Star-Formation Modes

Advisors: Vihang Mehta, Zahra Sattari

Galaxies appear to have undergone a major shift in how they grow roughly four billion years ago. At earlier epochs, many galaxies were clumpy, turbulent, and irregular, indicating that gas accretion and complex interstellar medium physics played a dominant role in shaping their evolution. More recently, star formation has become increasingly organized within stable, well-defined disk structures. The physical processes responsible for this transition remain one of the central open questions in galaxy evolution. Because the physics of these early clumpy systems is difficult to constrain directly, studying rare local analogs is essential. Wide-area, high-resolution imaging provides the ideal dataset to identify these uncommon objects, and such data are now becoming available with Euclid.

The ongoing citizen science project, Galaxy Zoo: Clump Scout 2 leverages the new Euclid imaging to greatly expand the sample of known clumpy galaxies in the nearby universe and simultaneously resolve the clumps. This dataset provides a prime opportunity to exploit the power of visual classification to train sophisticated machine learning techniques to develop robust methods for identifying clumps in galaxies. We invite PhD students to explore this unique citizen science-enhanced dataset of Euclid clumps to understand the evolution of the clump properties in galaxies over the past four billion years as well as their role in shaping the growth of galaxies. These results, in the context of expectations from simulations, will inform on how the mode of star-formation changes over cosmic time.

Constraining Clump Physics with Resolved Clumps in the Local Universe with HST + MaNGA

Advisors: Vihang Mehta, Zahra Sattari, Kalina Nedkova

Clumps are prevalent in star-forming galaxies in the early universe, yet the physical mechanisms governing their formation, growth, and survival remain uncertain. Competing scenarios include in-situ gravitational fragmentation of gas-rich, turbulent disks and ex-situ processes such as minor mergers. At high redshift, limited spatial resolution and sensitivity hinder precise measurements of clump-scale properties, making it difficult to distinguish between these pathways – we can instead look for analogs in the local universe.

The Galaxy Zoo: Clump Scout project identified a statistically significant sample of clumps in the local SDSS galaxies. An HST gap-filler program subsequently obtained high-resolution ACS imaging (F435W, F775W) of roughly 100 of these galaxies at 0.02<z<0.06, enabling individual clumps to be resolved at sub-kiloparsec scales. Critically, these galaxies also have integral-field spectroscopy from the SDSS-IV MaNGA survey, providing spatially resolved emission-line diagnostics and kinematic information.

We invite students to explore a multi-wavelength, spatially resolved analysis of the clump population by combining HST photometry with MaNGA spectroscopy and ancillary SDSS data. This dataset will be used to constrain the clump stellar masses, ages, and SFRs. Comparisons to theoretical expectations will provide quantitative constraints on models of clump formation and evolution.

FIRESIDE: Far InfraRed Extragalactic Survey and Instrument Design Exploration 

Advisor: Vivian U

Far-infrared observations are poised to revolutionize our understanding of early galaxy evolution and black hole-galaxy co-evolution. The Astro2020 Decadal Survey has highlighted the critical importance of a far-infrared probe mission to fill the gap in our multiwavelength observational capabilities. However, optimizing the design of such a mission requires a deeper understanding of far-infrared source distributions, line luminosity functions, and high-redshift black hole populations. The FIRESIDE project addresses these crucial knowledge gaps through a combination of semi-analytical modeling and empirical methods. By investigating extragalactic source confusion, fine structure line properties of gas, and high-ionization line properties of unobscured and dust-obscured black holes in the far-infrared spectrum at and beyond cosmic noon, FIRESIDE aims to inform the design of future far-infrared missions and unlock transformative science in extragalactic astronomy.

We seek a student who will focus on the empirical aspect of the project, e.g., using CLOUDY modeling to make predictions for far-infrared lines relevant to AGN and star formation. This work will involve developing model spectra and analyzing archival data from literature. The student's contributions will be crucial in determining the spectral line detectability for key far-infrared diagnostics of star formation, AGN, and interstellar medium properties, culminating in a manuscript that will be an essential deliverable for the far-infrared community as we prepare for the future probe mission.

Mapping Metallicity in Galaxy Mergers

Advisors: Vivian U, Thomas Lai, Lee Armus

Galactic outflows play a crucial role in shaping galaxy evolution, yet many questions remain about their impact on the interstellar medium and their driving mechanisms. Our JWST program (PID# 1717) aims to address these pressing questions on outflows by leveraging the unprecedented capabilities of MIRI MRS. By observing a sample of nearby luminous infrared galaxies known to host prominent shocked molecular outflows, we investigate the impact of feedback on the interstellar medium, the energy transport into circumnuclear regions, and the effects on dust geometry and metal distribution. This study will provide a holistic view of the molecular gas, dust, AGN activity, star formation, and metallicity in the central regions of ongoing galaxy mergers.

We seek a student who will focus on the metal distribution aspects of this project. The student will analyze MIRI IFU data and develop methods to map metallicity gradients in galactic nuclei, investigate correlations between metal distribution, outflow properties, and AGN strength, and contribute to our understanding of how feedback processes influence chemical evolution in galaxies. This work will be crucial in unraveling the complex interplay between galactic outflows, AGN feedback, and metal enrichment in different galactic environments.