Current Undergraduate Research Opportunities

Below are some options for current CMU undergraduates interested in doing research on campus with professors. Also, feel free to knock on doors or contact Professor Ryan for guidance. Send her an email 

Still unsure? Check out the Gelfand Center's features on Prof. Alison and Prof. Tristram-Nagle to get a sense of what it means to conduct research as an undergraduate!

Mohit Bhardwaj

• Exploration of Novel Radio Transients in Wide-sky Radio Surveys Project
• Investigating the Origins of Fast Radio Bursts through Multi-wavelength Data Analysis Project
• Development of Techniques for Radio Data Processing in Transient Searches Project
• Cosmic Web Mapping using Fast Radio Bursts

Dr. Mohit Bhardwaj
McWilliams fellow
Department of Physics,
Carnegie Mellon University
Office: 8301 Wean hall

Rupert Croft - Cosmology

Rachel Mandelbaum & Xiangchong Li - Observational cosmology

Gravitational lensing induces coherent distortions in the images of distant galaxies, resulting from the deflection of light by intervening mass, and the coherent distortion includes changes in galaxy shape ("shear") and changes in galaxy size and flux brightness ("magnification" ). This project concentrates on using galaxy image simulation and mock galaxy catalog to understand the potential systematic errors introduced by the magnification effect in shear estimation and the related cosmological analysis.

Alex Malz & Rachel Mandelbaum - Observational cosmology

We seek a student for an important project to inform strategic decisions for upcoming big-data galaxy survey missions by exploring data compression schemes for high-dimensional per-galaxy probability distributions representing the nontrivial uncertainty in their physical properties. Using the qp software library (Python), the student will expand upon the precursor experiment of Malz+ 2018, balancing the resource footprint to store these data products, the computational expense to decompress them for downstream analysis, and the preservation of the complex information encapsulated by the uncompressed probability distributions.

Kostya Malanchev & Rachel Mandelbaum - Observational astrophysics

1. Search for faint high-proper motion stars. Thanks to Gaia, we currently know of a few hundred stars moving in the sky faster than an arcsecond per year. In this project, the student will analyze the low-mass star population near the Sun and look for them using shift-and-stack technologies. Knowledge of Python is preferable, but not mandatory.

2. Search for fast transients in Zwicky Transient Facility (ZTF) high cadence data. The student will analyze a ZTF data release to find bright and fast transients in the variable sky. We could find gamma-ray burst afterglows, self-lensing events in binary systems, stellar flares, and other types of objects. Knowledge of Python is preferable, but not mandatory. 

Tiziana Di Matteo - Astrophysics & Cosmology

Simulating the first galaxies and black holes at the cosmic dawn

Richard Griffiths - Astrophysics & Cosmology

Investigation of gravitationally lensed images in Hubble Space Telescope data, with the goal of constraining the properties of dark matter using gravitational 'folds'.

Tina Kahniashvili - Theoretical Cosmology

Topic 1: Gravitational waves from the early universe
Topic 2: Cosmological magnetic fields: their origin, evolution, and signatures

Brendan O'Connor- Obervational Astrophysics

Topic 1: Classification of optical transients (e.g. supernovae, tidal disruption events) discovered with the Dark Energy Camera (DECam)

Topic 2: Study of the host galaxies of optical transients discovered with DECam

Topic 3: Classification of unidentified Galactic X-ray sources discovered by the Swift Deep Galactic Plane Survey

Topic 4: Theoretical study of gamma-ray burst jets and/or populations of gamma-ray bursts

For more information contact:
Brendan O' Connor 
Email
https://brendanoc95.wixsite.com/brendanoconnor/

Antonella Palmese - Observational Astrophysics and Cosmology

• Machine Learning Classification of astronomical transients.
• Follow-up of gravitational wave events with optical telescopes.
• Gravitational Wave Standard Siren cosmology.

Jeff Peterson - Radio Astronomy and Cosmology Instrument Development

Students design and build radio astronomy receivers and use these to search for Fast Radio Bursts and the origins of the first stars which formed 200 million years after the Big Bang. We deploy these instruments to remote sites in Canada, South Africa, and desert islands such as Isla Guadalupe and Marion Island.

• Simulations of binary stars and the white dwarfs, neutron stars, and black holes they produce.
• Astronomical software development
• Predictions of stellar-origin populations for electromagnetic and gravitational-wave surveys. 

• Galaxy cluster mass reconstruction with machine learning.
• Simulating dark matter and baryons with the cosmological code HYPER.
• Modeling cosmic dawn and the epoch of reionization with semi-numerical code AMBER.

Shila Banerjee

We are looking for motivated undergraduates to conduct theoretical and/or computational research in the area of biological physics. Possible projects include: modelling the growth and replication cycle of bacteria, phase transition in cells, computational modelling of cell mechanical properties. No prior knowledge of biology is necessary and the research projects can be conducted remotely. Prospective students are encouraged to browse through work done in our group.

Markus Deserno

My group is interested in theoretical and computational biophysics, with a focus on lipid membranes. Typical theory projects focus on membrane elasticity, shape/geometry, phase behavior, and the implications of lipid asymmetry across the leaflets of a bilayer. Computational projects approach the same subjects via molecular dynamics simulations of highly simplified models, or investigate how to measure a membrane’s elastic parameters by analyzing its fluctuations. For details, check out some of our recent work on our webpage If you’re interested in any of this, talk to me. As a prerequisite, you do not need a background in biology, but some familiarity with thermal/statistical physics is very useful. For computational projects, some experience with programming is needed, but you definitely don’t have to be seasoned coder.

John Nagle

Fangwei Si

Our lab's drive is to discover “biological laws” that can help us understand living systems in a quantitatively precise way. Towards this goal, we develop/adapt tools, do rigorous measurements, and define new concepts. We are currently searching for simple yet fundamental rules connecting the complicated form of bacterial cells and their fitness in different environments. Please check out the lab website for more descriptions of our research. If you are curious about how living systems emerge from non-living matter and want to get your hands dirty in a wet lab, you are always welcome to contact us!

Stephanie Tristram-Nagle

The Tristram-Nagle lab uses x-ray diffuse scattering (XDS) collected at the Cornell High Energy Synchrotron Source (CHESS) or with the Xenocs Xeuss 3.0 at CMU to study the interaction between antimicrobial peptides and lipid model membranes that mimic real bacterial and eukaryotic membranes. These peptides are a promising new antibiotic to overcome the problem of bacterial resistance leading to super bugs. Physics students will learn how to collect and analyze x-ray data, make graphs and write results into papers. We also use circular dichroism to determine the secondary structure of the peptides as they interact with lipid membranes. Dr. Tristram-Nagle has openings for in-person students. WEBsite: https://www.cmu.edu/biolphys/jfstn/ 

Newell Washburn

My group is interested in understanding the physics of aging using both experimental and computational methods in collaboration with Prof. Fabrisia Ambrosio at the University of Pittsburgh. The current focus is on modeling transcriptomic changes in muscle stem cells to elucidate alterations in information flow through the gene network as a function of organism age. Our computational tools include machine learning, information theory, and by drawing analogies with classical and statistical mechanics. Email

Randy Feenstra - Experimental Condensed Matter

Simulation and/or curve fitting of spectroscopic data from a scanning tunneling microscopy or a low-energy electron microscope.

Steve Garoff - Applied Soft Matter Physics

Experimental projects on a wide variety of topics in wetting and the behavior of complex fluids

Sara Majetich - Small Angle Neutron Scattering of Magnetic Nanoparticles

This computational project will compare theoretical models of magnetization patterns in magnetic nanoparticles with data from small angle neutron scattering (SANS) experiments. Just as x-ray diffraction arises from the Fourier transform of the electronic charge distribution in a crystal, neutron scattering can be used to reveal the nanoscale magnetization. Working with collaborators at NIST and Oberlin College, the Majetich group has investigated many types of magnetic nanoparticles using SANS with polarization analysis. Here neutrons are polarized “spin up” or “spin down” before scattering, and afterward they are analyzed to see if there have been spin flip events due to the magnetization in the nanoparticles. SANS with polarization analysis was used to demonstrate non-uniform magnetization within nanoparticles [1]. When a magnetic field is applied, surface spins may cant reversibly, depending on the temperature and magnitude of the field. For magnetite, Fe₃O₄, the form factors of a sphere plus a spherical shell were sufficient to explain the experimental results, but with manganese ferrite, MnFe₂O₄, the magnetization pattern is clearly more complex. The approach will be to assume a magnetization pattern for the nanoparticles, divide them into two-dimensional slices, take the Fourier transforms, and add up the scattering contributions from the different slices. There is already a lot of experimental data that will be useful for comparison and model refinement. 

1. Visualizing Core-Shell Morphology of Structurally Uniform Magnetite Nanoparticles, K. L. Krycka, J. A. Borchers, J. A. Borchers, Y. Ijiri, W. C. Chen. S. M. Watson, M. Laver, T. R. Gentile, S. Harris, L. R. Dedon, J. J. Rhyne, and S. A. Majetich, Phys. Rev. Lett. 104 207203 (2010); doi: 10.1103/PhysRevLett.104.207203.

Simran Singh - Experimental Condensed Matter

Spin transport in atomically thin quantum materials

Mike Widom - Condensed Matter Theory

Professor Widom models the structure and thermodynamics of complex crystal structures using a combination of quantum mechanics and statistical mechanics. Highly motivated students with strong computer skills are welcome to inquire about a research position.

Roy Briere - Experimental Particle Physics

Belle II experiment at KEK; various software projects

Matteo Cremonesi - Experimental Particle Physics

Valentina Dutta - Experimental Particle Physics

CMS experiment at CERN and Light Dark Matter eXperiment (LDMX) at SLAC.

Possible projects on CMS vary from data analysis related to searches for new physics including the use of machine learning, to hands-on instrumentation work. LDMX is an exciting prospective experiment to search for dark matter lighter than the proton mass, and is in the development phase. Possible projects on LDMX include the analysis of simulated data sets and software development.

Diana Parno - Experimental Neutrino Physics

COHERENT experiment: Our group is measuring neutrino-nucleus scattering to test the Standard Model, probe nuclear physics, and understand future supernova measurements. We have projects to help build and analyze data from a heavy-water detector that will measure the flux of neutrinos from our source; to simulate the production of radioactive isotopes in our source; and to study neutron backgrounds with a dedicated MARS detector.

KATRIN experiment: Our group uses the radioactive decay of tritium to make world-leading measurements of the neutrino mass scale. We have projects to help design a small experimental setup for studying the way tritium adsorbs on experimental surfaces and causes backgrounds, and to better understand some of those backgrounds via data analysis.

Manfred Paulini and John Alison - Experimental Particle Physics

CMS experiment at CERN with various projects from hands-on instrumentation work to data analysis and also event classification using machine learning