2026 Research Projects
Investigating the Requirements for the Detection of Filaments with Weak Gravitational Lensing
Advisors: 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.
Exoplanet Occurrence Rates in the TESS Continuous Viewing Zones
Advisor: Kevin Hardegree-Ullman
The NASA Kepler mission rapidly and drastically grew our understanding of exoplanet populations and statistics. However, the narrow focus on Sun-like FGK stars curtailed our ability to fully study the population of planets around the most common stars in our galaxy, M dwarfs. TESS continues the Kepler and K2 legacy, expanding our search for planets to the entire sky. The TESS Continuous Viewing Zones (CVZs) offer a unique opportunity to expand the Kepler population studies of FGK and M stars with TESS in two regions of the sky with much longer time baselines than individual 27-day TESS sectors. A visiting graduate student would work with our superstar exoplanet demographics team to (1) search for planets in the CVZs using multi-sector TESS data (2) vet exoplanet candidates (3) run injection-recovery tests and (4) compute exoplanet occurrence rates. There are several existing open-source tools to work with TESS data, so the student would identify and adapt these tools for the TESS CVZ project. Prior experience with transiting exoplanets and coding knowledge in Python is strongly recommended.
What's hiding in the hottest Jupiters?
Advisor/s: Kevin Hardegree-Ullman and Aurora Kesseli
The discovery of the first exoplanets completely changed our views of how planets form, specifically Jupiter-sized planets orbiting very close to their host star. Signs of the history and evolution of these planets are trapped in the chemical composition of the planetary atmospheres. For planets that form farther out and migrate in, we expect the amount of refractory material to be lower than the stellar abundance, but if the planet formed closer in, we might expect the refractory abundances to be higher than the stellar values. However, even in our own Solar System, it is not clear how the giant planets formed and acquired their abundances. Our team conducted a survey with the SOAR Telescope to obtain optical (~380-680 nm) transmission spectra of about 15 hot Jupiters above 1700 K which were observed in order to constrain atmospheric oxygen and metal abundance through measurement of titanium oxide, vanadium oxide, and sodium features. We expect a visiting graduate student to work with our team to process our data and constrain atmospheric properties (e.g. abundances, Rayleigh scattering, clouds/hazes) of these hot Jupiters by comparing our transmission spectra to different publicly available atmospheric model grids. Familiarity with Python or other programming languages commonly used in astronomy is recommended.
Galaxies in the Early Growth Phase with JWST and ALMA
Advisor: Andreas Faisst
We seek a student to work on combining the extensive multi-wavelength imaging and spectroscopy from ALMA and JWST to conduct a range of studies as part of the ALPINE ALMA large program on the COSMOS field. The JWST data includes cycle 1 NIRCam imaging data from 255h COSMOS-Web as well as data from a 60h cycle 2 NIRSpec/IFU program. The sample includes main-sequence galaxies at z = 4 – 6 and provides the currently largest sample with observations from UV to far-IR including JWST optical lines. Other archival data can be added. A possible project could focus on the study of internal dust attenuation of the galaxies or their stellar population distribution via resolved SED fitting and spectroscopy. The findings can then be related to the evolution of galaxies on the z ~ 5 main sequence and their far-IR and [CII] properties and dynamics. The student would have access to all ALPINE (including JWST follow-up) data. Ideas for other projects related to the above are very welcome.
Deciphering the Growth of Massive Galaxies with Euclid
Advisor: Andreas Faisst
The dominant mass growth mechanisms of very massive (mostly quiescent) galaxies are still under debate. Accretion of mass in the form of minor satellites could be an avenue next to internal star formation or major mergers. Such cases will also alter the sizes of the galaxies. The first images from JWST already showed the abundance of globular clusters and dwarf galaxies around massive galaxies in the low-redshift universe (z~0.5). Euclid covers a large area for statistical studies and benefits from superior surface brightness sensitivity. We seek a student who is interested in studying the circum-galactic medium around massive galaxies at z < 1 to understand better the contribution of satellite populations to their mass and size growth. A possible avenue is to stack light profiles derived from (public) Euclid images (+ any ancillary data) of selected massive galaxies. We also encourage students with theoretical background to apply - specifically to compare and explain the abundance (or absence) of satellite populations in the context of cosmological simulations.
A study of dark matter via galaxy-galaxy lensing in Euclid
Advisor: Andreas Faisst
Galaxy-galaxy strong lensing is a unique tool to constrain the dark matter fraction of individual galaxies. Such lens systems will be found abundantly in the new Euclid data. We seek a student to help developing a tool to extract the physical properties of the lens (massive foreground galaxy) and the source (lensed background galaxy) in Euclid imaging and slitless grism spectroscopic data, and to perform the first measurement of dark matter. This project involves several tasks, such as the structural modeling of the lens system to constrain the SEDs of lens and source and the subsequent extractor of their spectra. We will use public Euclid data, therefore you do not have to be part of the Euclid consortium.
Exploring the Dusty Universe with CHAMPS
Advisor: Andreas Faisst
CHAMPS is a 144h ALMA Large program in cycle 10 covering the 0.2 square-degrees of the COSMOS-Web JWST field with 1.2mm observations. The program aims at detecting the most dusty sources in the high-redshift universe. We seek a student to work on projects related to the CHAMPS ALMA data as well as JWST (and other) ancillary data. Possible projects include the study of the first heavily dust-obscured galaxies, constraining the ISM masses of quiescent galaxies, or studying the relation between stellar mass, star formation, and ISM mass across cosmic time from individual detections and from stacking. The student would have access to all ALMA and JWST data in the COSMOS field. Other ideas for projects related to these data are very welcome.
Resolved PAH Emission in z = 1 galaxies
Advisor: Andreas Faisst
We seek a student to work on a project related to an accepted JWST/MIRI MRS cycle 3 program to study the resolved PAH emission in z=1 galaxies. The galaxies are selected to be face-on, thus allow the examination of changes in the PAH emission lines in a spatially resolved manner across the galaxies. Possible projects could involve: (i) optimization of pixel-by-pixel mid-IR SED fitting for this project to derive kpc-resolved PAH line ratios; (ii) the measurement of grain sizes across the galaxies; (iii) the characterization of ionization properties in the galaxies from Ne lines. Other ideas for projects along these lines with these data are welcome.
Testing the Method of Cluster Redshifts for Future Surveys
Advisor: Andreas Faisst
Large area surveys often lack the photometric coverage for accurate photometric redshifts. Or, some sources, such as dust-obscured star forming galaxies detected with Herschel or ALMA lack optical counterparts, making it difficult to derive redshifts. Cluster redshifts (redshifts based on the clustering of sources) provide a method to derive a redshift distribution for a population of galaxies via their large-scale clustering on the sky. The only input are positions and a selection function for the training sample. This method could be applied to large area surveys (such as with Euclid or Roman) to provide alternative redshift distributions to classic photometric redshifts or redshifts derived with machine learning techniques. We seek a student for a project which aims at (i) characterizing the biases of such a technique by comparisons to dark-matter-only simulations (readily available), and (ii) applying this method to various fields including the COSMOS field where accurate photometric and spectroscopic redshifts are available for training and testing.
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
Advisor: Vivian U
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 Cycle 1 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.
Measuring Star Formation, Black Hole Growth and Feedback in Luminous Infrared Galaxies with JWST
Advisors: Lee Armus, Thomas Lai, Vivian U
Luminous Infrared Galaxies (LIRGs) generate their enormous power through intense starbursts and the fueling of Active Galactic Nuclei (AGN). With the Great Observatories All-sky LIRG Survey (GOALS), we are characterizing over 200 low-redshift LIRGs across the electromagnetic spectrum, from the X-rays through the radio. A key part of GOALS is the study of how stars form and black holes grow under these extreme conditions, by observing the atomic and molecular gas and dust at high resolution using ground and space-based observatories.
We have been awarded an Early Release Science, Large Cycle-2, and a number of other JWST programs to study LIRGs in the local universe with MIRI, NIRSpec and NIRCam. The successful candidate will work directly with the GOALS team to reduce, analyze and publish these JWST data, in concert with other ground and space based datasets (e.g. HST, ALMA, VLA, Keck, VLT) specifically to characterize star formation, AGN feedback, shocks, and the properties of the atomic and molecular ISM in LIRGs.
Hunting Dust Properties of Extreme Star-Forming Regions
Advisor: 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.
Deciphering galaxy evolution with emission line galaxies using JWST grism spectroscopy
Advisor: Vihang Mehta
JWST slitless spectroscopy mode is revolutionizing our understanding of galaxy evolution at high redshifts, especially in the important low-mass regime, by providing unprecedented access to study the physical properties the stellar and ISM content of galaxies in great detail at high-redshifts.
The JWST Cycle 1 program, PASSAGE (GO1571, PI Malkan), has acquired up to 400 hours of NIRISS grism data over several tens of independent fields in up to 3 filters, spanning 1-2.3 micron and covering a total area up to 280 sq. deg. This program provides an unbiased spatio-spectroscopic dataset for several thousands of galaxies, including key optical emission lines (such as Balmer lines, [OIII], [OII]), across a wide redshift range (z=1-3.5). This dataset enables a wide range of galaxy evolution science including the time evolution as well as spatially resolved analysis of galaxy physical properties (such as metallicities, emission line strengths, ionization states, dust content, etc.), studying galaxies at the epoch of reionization, and discovery of rare, bright objects.
We seek students to leverage this rich JWST grism dataset to infer the stellar and nebular properties of galaxies and ultimately, study how galaxies grow and evolve over cosmic time. The student will have access to the reduced PASSAGE data and would be welcome to tackle any of the listed or other topics related to galaxy evolution enabled with these data.
Maximizing Exoplanet Direct Imaging with Machine Learning
Advisor: Tiffany Meshkat
Exoplanet direct imaging is a powerful method for detecting and characterizing giant planets at wide separations from their host stars. This technique relies primarily on coronagraphic imaging with ground- and space-based telescopes to suppress starlight and reveal faint planetary companions. Even in the most favorable cases, exoplanets detected via direct imaging are typically tens of thousands of times fainter than their host stars. To overcome these challenges, we use a combination of observational strategies and advanced post-processing techniques to isolate the planetary signal from the bright stellar halo and quasi-static speckles.
In this project, we will analyze Keck Observatory coronagraphic observations of known exoplanets, particularly the HR 8799 planetary system, to refine image processing techniques using machine learning. We will use machine learning to help generate a more realistic PSF model of our star to subtract away and reveal potential planetary companions. By training algorithms on real data, we aim to optimize speckle suppression and improve the detectability of faint planets. Once validated on known planetary systems, this pipeline will be applied to a broader Keck direct imaging dataset to conduct a systematic search for new exoplanets. A successful outcome could lead to the discovery of previously undetected planetary companions, enhancing our understanding of exoplanet demographics and formation. This project will provide hands-on experience with high-contrast imaging techniques, astronomical data analysis, and machine learning applications in observational astrophysics.
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, image processing, and spectral fitting, contributing to a deeper understanding of dust and star formation in low-metallicity galaxies.
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.
Resolving the Dynamic Interstellar Medium with Infrared Echoes around Cas A
Advisor: Jacob Jencson
The content and structure of the interstellar medium (ISM) plays an influential role in the formation of stars and overall evolution of galaxies. In turn, the ISM is also shaped by the massive stars formed out of its gas and dust and the energetic supernovae (SNe) they produce. The infrared echoes around the young SN remnant Cassiopeia A provide a unique laboratory to explore the effects of a high-energy burst of SN radiation as it interacts with ISM dust in real time. Using recently obtained JWST time-series observations, this program exploits the apparent motion of these echoes in NIRCam imaging to map the 3D structure of the echoing dust clouds and precisely measure the changes in their compositions induced by the passing SN radiation in MIRI/MRS spectroscopy. The graduate student will primarily work with Dr. Jencson at IPAC to reduce and analyze the MIRI data and lead a publication on detailed modeling of the time-resolved spectra. As a member of the team, the student will also collaborate with JWST instrument scientists at the Space Telescope Science Institute and dust-modeling experts at NASA/Goddard.
Focusing the Eye of Roman on the Inner Galaxy
Advisor: Jennifer Sobeck
The next NASA Flagship Mission, the Nancy Grace Roman Telescope, is scheduled to launch in Autumn 2026 and will enable revolutionary discoveries in the areas of dark energy, exoplanets, and infrared astrophysics. The onboard grism and prism elements will allow the Wide-Field Instrument (WFI) to perform slitless, multi-object spectroscopy across the entire field of view. These instruments will play a key role in the Roman-Designated Galactic Bulge Time Domain and Galactic Plane General Astrophysics Surveys, which should produce stellar property and other information for billions of stars over the mission lifetime.
The graduate student will undertake preparatory work for the Roman mission and generate synthetic stellar spectral libraries for the grism and prism instrumentation. They will also employ mathematical/learning methods to determine information content in these spectra. The student will collaborate with other experts across the Roman Community including personnel from IPAC and STScI.
Galaxy Survey Enhancements with Deep Learning
Advisor: Shoubaneh Hemmati
The success of many of the upcoming large cosmology missions (e.g., LSST, Roman, Euclid, SPHEREx) relies on the precise measurements of the redshifts, shapes, and other physical properties of galaxies. These measurements often require a joint processing of the observations and the higher the spatial and spectral resolution, wavelength coverage, and depth of these observations, the more information they entail. Given the wealth of the galaxy data today and advancements in image processing with deep learning, huge improvements for future surveys and their combinations can come about using data-driven approaches.
Through this project, we will design and optimize multi-band image enhancement deep learning structures and explore the extent of spatial/spectral resolution boosting, denoising, and in-filling of hyper-spectral images for future large galaxy surveys by training on the deepest existing multi-band observations. We will quantify the gain in the estimation of various physical properties given the enhanced data products.
Toward eta_Earth: Building a Framework to Combine Kepler and Roman exoplanet demographics
Advisor: 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.
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.
Modern Post-Processing for the Modern Age: Model-based Calibration for JWST images
Advisors: Alexandra Greenbaum
JWST has already delivered many superb images of astronomical scenes, exceeding expectations on imaging stellar companions and young planetary systems. Given the richness of data and telemetry collected, even more could be possible. To resolve structure very close-in to the center of the PSF often requires dedicated calibrations (PSF reference) to get a snapshot of the instrument response function and subtract it out. This is routinely done for coronagraphic, direct imaging, and aperture masking interferometry (AMI). The regular wavefront measurements that that mission makes publicly available and can provide strong priors on characterizing and subtracting the PSF. Future missions, like the Roman coronagraph and HWO can also benefit from realistic instrument models for data reduction and performance.
This project will extend an existing instrument model for NIRISS direct and NIRISS AMI to include detector level effects and test this technique on real JWST data. The student will work with Dr. Greenbaum and collaborators to update the instrument model and reduce existing JWST data taken with the NIRISS instrument to compare with existing techniques.
Studying dwarf galaxies at high redshift using JWST and HST
Advisors: Anahita Alavi
JWST continues to amaze us by gazing at faint galaxies from the epoch of reionization (EoR). Nevertheless, with many hours of observations, the fundamental question that remains is understanding the key sources of ionizing radiation during reionization era. To address this, our focus must shift to lower redshifts, where ionizing radiation can traverse IGM.
Dwarf galaxies are expected to play a substantial role in ionizing the IGM. As part of an approved JWST AR program, a prospective graduate student is expected to incorporate the JWST NIRISS grism data of Abell 2744 galaxy cluster, with existing deep HST/WFC3 UV data. The goal is to investigate how effective are dwarf galaxies in producing ionizing photons at cosmic noon. Abell 2744 is a massive galaxy cluster which provides large gravitational lensing magnification. This enables the study of faintest galaxies that would otherwise be challenging to detect. This cluster is part of Hubble Frontiers Fields program with JWST ERS data from GLASS, and rich ancillary data from HST and many other ground-based observatories.
A successful visiting student is expected to use H-alpha emission line measurements from the JWST/NIRISS grism spectra and UV luminosity from the HST/WFC3 UVIS imaging to measure the ionizing photon production efficiency. This project may involve working with NIRISS grism spectra and spectral fitting, measuring galaxy properties via SED fitting, and using gravitational lensing tools to estimate lensing magnifications.
The prospective student will collaborate with a group of experts at IPAC and UC Riverside. The student will lead the scientific analysis and the publication (first author). Students with experience in working with spectra, especially JWST grism spectroscopy, are encouraged to apply.
