Undergraduate Research Openings | Department of Physics

Faculty Name	Type	Research Area	Research Title	Research/Project Short Description	Desired Skills	Type of Position	Contact Info	Available to ASU Online Students
Philip Mauskopf	Experimental	Nanoscience and Materials Physics	Superconducting quantum devices	Work on a variety of superconducting devices including high frequency qubits, single photon detectors, microwave resonators and kinetic inductance detectors.	Circuit design and simulation, 3D electromagnetic design and simulation, solidworks or othe CAD, python, VHDL	Credit, Paid, Volunteer	[email protected]
Ricardo Alarcon	Experimental	Cosmology, Particle, and Astrophysics	Development of diamond-based detectors for applications in nuclear and particle physics.	The project consists of instrumenting and testing diamond-based detectors using radioactive sources.	PHY-333	Credit, Paid, Volunteer	[email protected]
K.T. Tsen	Experimental	Biological and Soft Matter Physics	Selective photonic disinfection of bacteria and other pathogens in wound by using femtosecond laser irradiation	In this translational research project, we will employ femtosecond lasers to kill the bacteria as well as other pathogens in a wound while leaving the tissue unharmed.	Basic knowledge on optics, lasers and Arduino for programming two dimensional scanning system with the motor drives.	Volunteer	[email protected]
Antia Botana	Theoretical	Nanoscience and Materials Physics	Electronic structure of quantum materials	Projects for undergraduate students related to the theory of quantum materials are available. The primary goal consists on the application of computational methods to understand how electrons behave in these systems. The focus is on two basic phenomena: magnetism and superconductivity.	Quantum mechanics, programming skills.	Credit	[email protected]
Simon Foreman	Theoretical	Cosmology, Particle, and Astrophysics	21cm Cosmology and Large-Scale Structure	What are the fundamental laws that determine the birth, evolution, and contents of the universe? The field of “21cm cosmology” aims to help answer this question, by measuring faint radiation from distant clouds of hydrogen gas, relating the distribution of these clouds to the underlying “large-scale structure” of the universe, and using the statistical properties of this structure to learn about the universe and fundamental physics. Projects are available to investigate specific topics in 21cm cosmology, likely involving a mixture of theoretical and computational work. The precise topic is to be determined, but possibilities include: forecasting the sensitivity of the upcoming CHORD telescope in measuring the the cosmic large-scale structure; comparing the theoretical expectation for telescope noise to detailed simulations; developing mathematical techniques to account for filtering of foreground signals in theoretical predictions; implementing new techniques for simulating large-scale clustering; and contributing to data analysis infrastructure for the currently-operating CHIME telescope (https://chime-experiment.ca/en).	Familiarity with Fourier transforms, basic statistics, and scientific computing in Python or a similar language. Familarity with concepts in astronomy or cosmology is welcome, but not required.	Credit, Paid	[email protected]	No
Quan Qing	Experimental	Biological and Soft Matter Physics, Nanoscience and Materials Physics	Integration of Raman spectrometer with quantum conductance measurement for multi-parameter single-molecule identification	How do charges transport through a single molecule sandwiched between two metal electrodes? It has long been shown that the conductance strongly depends on the molecule’s structure, and the interface between the molecule and the metal surface. But such measurements have proved to be very delicate and conflicting results have been all over the map. For example, DNA molecules have been shown to be insulators, conductors as well as superconductors in different experiments. Indeed, with the rapidly expanding studies of conductivity of biomolecules, where hydrogen bonds, pi-pi stacking, hydrophobic interactions, and allosteric structures are actively involved, more and more results have been shown to fall outside the realm of conventional quantum tunneling theories. New developments at the intersect of physics and biology reveal a wide open field for exploration, promising new paradigms of how charges can transport in a 3D complex molecular systems, as well as label-free biosensors based on the dynamic conductance measurements. However, all studies have been significantly limited by the techniques for constructing the metal-molecule-metal structure, mostly based on scanning tunneling microscope, mechanical break junctions, or brute-force top-down lithography. All measurements so far rely on the random diffusion and binding of molecules, and statistical analysis of hundreds to thousands of repetitive operations. It is extremely challenging to control the position and states of the molecule bridge between electrodes, and the operation typically require strict environment control and with high technical skills. Is it possible to construct a platform for highly reproducible measurements that brings together single molecule delivery, conductivity measurements and molecule structure characterization, such that a broad range of biomolecules can be easily investigated under physiological conditions? The goal of this project is to develop a microchip-based universal platform that integrates nanopore, tunneling junction and Raman spectroscopy for multi-parameter investigation of different biomolecules in physiological conditions during enzymatic activities. The student will help the development of a customized Raman spectrometer and integrate with a nanoelectropore system to perform preliminary experiments on correlated Raman and quantum conductivity measurements on model molecules ranging from simple small molecules such as 4-mercaptobenzoic acid, to double-strand DNA molecules, and even larger proteins that can form molecule bridge through antibody-antigen interactions.	3D modeling, optics, electronics, programming	Volunteer	[email protected]	No
Robert Kaindl	Experimental	Nanoscience and Materials Physics	Broadband Ultrafast Probes of Quantum Materials	Our research explores fundamental and applied physical phenomena in correlated and nanoscale quantum materials using advanced ultrafast tools. Femtosecond light pulses provide unique opportunities to perturbatively resolve fast dynamics and interactions in these materials, and they can drive materials into new transient or metastable regimes via intense excitation. We are developing a new laboratory for tailored driving and detection of quantum and collective excitations using broadband terahertz, mid-IR, and visible light pulses as well as probing of electronic structure dynamics via time- and angle-resolved photoelectron spectroscopy (trARPES). This effort provides many project opportunities, spanning initially the range from literature research and simulations, fabrication and characterization of 2D and correlated samples, to the design and development of nonlinear optical setups in the terahertz, mid-IR, and extreme-UV regimes. Moreover, our research is closely aligned with the ASU CXFEL program making possible laser-science projects connected to the femtosecond X-ray source and pump-probe setup that is currently under commissioning. At a later stage, the student can also get involved with the first time-resolved THz/mid-IR and ARPES experiments in our group to investigate the dynamics of quasi-particles and order parameters as well the properties of light-induced phases in two-dimensional, topological, and superconducting materials.	Interest in condensed matter physics, optics/lasers, programming, and data analysis. Prior experience in any of these areas is useful but not required.		[email protected]	No
Jingyue Liu	Experimental	Nanoscience and Materials Physics	Electrochemical Conversion of Molecules for Sustainable Energy	Design and develop nanoscale architectures for electrochemical conversion of molecules with a focus on producing clean energy; understand the fundamental processes of fabricating functional structures at the single-atom limit; and correlate synthesis-structure-performance relationships.	Strong desire to learn experimental skills in materials synthesis; experiences in handling chemicals and routine lab skills in a wet chemistry lab.	Volunteer	[email protected]	No
Mouzhe Xie	Experimental	Biological and Soft Matter Physics, Nanoscience and Materials Physics	Experimental Quantum BioSensing (EQuBS) lab -- quantum metrology and high precision measurement using nitrogen-vacancy defects in diamond crystal	As a new lab, we always have cross-disciplinary research projects available to postdocs, graduates, and undergrads! Please refer to https://sites.google.com/view/equbs-lab/opportunities for the latest update. Please email Prof. Mouzhe Xie ([email protected]) for inquiries and to discuss details.			[email protected]	No
Rogier Windhorst	Experimental	Cosmology, Particle, and Astrophysics	Cosmology and Astrophysics Research with the Hubble and James Webb Space Telescopes	The student will study current hot topics in cosmology, the epoch of cosmic reionization, star-formation in a cosmological context, galaxy formation and evolution, gravitational lensing via galaxy clusters and cluster caustic transits, and the growth of super-massive black holes in the centers of galaxies. The student will will get hands-on experience and learn how to reduce and analyze Hubble and JWST data. We meet with the whole research group once a week (currently Fr. 1:30-3:30 pm in GWC-505) to assign projects, train students, monitor progress, and discuss specific research aspects, skills, and progress on papers.	Essential Skills: Recommended is some experience with Mac OS and/or UNIX, and image processing, although not essential for UGs Animation: Beginner C: Beginner or better. Python is preferred CAD: None Database: Beginner or better GPS: None/No Preference HTML: Beginner or better Image Processing: Beginner or better Java: Beginner or better Linux: Beginner or better Macs: Beginner or better Statistics: Beginner or better Additional computer knowledge, programs, languages: Java, IDL, IRAF/STSDAS, and/or Python experience will come in handy, or can be learned as you go.		[email protected]	No
Jose Menendez	Theoretical	Nanoscience and Materials Physics	Semiconductor Equations using Polylogarithms	The purpose of this research is to develop an approach to the solution of the coupled semiconductor equations that transitions smoothly from the Boltzmann to the Fermi Dirac limit and is capable of simulating the operation of semiconductor devices at room and cryogenic temperatures. The approach must be compatible with current algorithms for the numerical solution of the equations.	A background in solid-state physics and programming can speed up the research, but is not required. The interested party can find a brief introduction to polylogs in semiconductor physics in M. D. Ulrich, W. F. Seng and P. A. Barnes, Journal of Computational Electronics 1, 431 (2002).	Volunteer	[email protected]	No
Siddharth Karkare	Experimental	Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics	Characterization of Novel Photoelectron Emitters in High Electric Fields	Brightness of electron beams generated from photoemitters limits the performance of most linear accelerator applications, ranging from small meter-scale electron microscopes to large km-long particle colliders and x-ray free electron lasers. In this project, you will work on a unique DC electron gun with a cryogenically cooled cathode to test the performance on novel, nanostructured photo emissive materials under extreme electric fields to generate record high brightness electron beams for various applications. Students working on this project can continue this project towards their PhD thesis. Due to the available funding criteria US citizens or Permanent residents will be strongly preferred.		Credit, Paid	[email protected]	No
Siddharth Karkare	Experimental	Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics	Development of Ultrafast Electron Microscopy	In this project you will develop the ability to perform Ultrafast Electron Diffraction - a novel technique used to study femtosecond scale structural dynamics of atomic lattices and molecules - using the ASU DC cryogenic electron gun. You will also design and develop novel electron guns for advanced electron microscopes which will allow performing ultrafast electron microscopy with unprecedented spatial and energy resolution. The project involve working with and designing high-voltage-high-field electron guns and cryogenic cooling systems under ultra-high-vacuum conditions. Such guns are not only useful to generate electron beams for ultrafast science, but will also ower the next generation particle colliders and x-ray free electron lasers. Students working on this project can continue this project towards their PhD thesis. Due to the available funding criteria US citizens or Permanent residents will be strongly preferred.		Credit, Paid	[email protected]	No
Steve Pressé	Experimental	Biological and Soft Matter Physics	From bacterial hydrodynamics to bacterial predator-prey dynamics	We have previously shown that the bacterial predator, Bdellovibrio bacteriovorus, hunt their prey, E. coli, by leveraging passive hydrodynamic forces rather than actively seeking out their prey through, say, chemical signaling. In particular, hydrodynamic forces can become manifest when predators move near surfaces forcing them to co-localize with prey. Here we propose to take this idea a step further and investigate the predator's hunting efficiency when it is part of a population of predator and prey within the microbiome of a living organism (in this case, the worm c. elegans). In living organisms, questions as to how predators hunt abound. For example we hope to address these questions: 1) how do we go about quantifying the kinetics of predation when predation occurs within the gut of an organism?; 2) how does the effect of physical confinement within the gut of c. elegans impact the predator's predation efficiency?; 3) what kind of (non-equilibrium statistical mechanical) theories are required in order to describe predation dynamics from individual gut colonization events, to saturation involving tens of thousands of bacteria, while describing fluctuations in levels of predator and prey within a living organism's gut?; 4) can we ever use this knowledge to engineer the predator as a living antibiotic?		Paid, Volunteer	[email protected]	No
Steve Pressé	Theoretical	Biological and Soft Matter Physics, Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics	Statistical mechanics meets AI/ML	We live in an age where data abound from biological physics to astronomy and there is an explosion of new tools (AI/ML) inspiring us to think quantitatively about these data. Yet these tools, often inspired by developments in Mathematics and CS, can be black boxes and not suitable for applications within the Natural Sciences. Our goal is to advance computational tool, appropriate for the Natural Sciences, critical in gathering insights on life's processes observed through advanced microscopy techniques or astronomical events observed using modern telescopes. In particular, we leverage tools from AI and machine learning, many grounded in computational statistics, to glean insights about our physical universe otherwise unavailable using traditional analysis techniques. For example, of particular interest, is resolving with higher resolution objects further away from our planet from very limited photon budgets or unraveling the collective dynamics of molecular machines (i.e., transcription factors) operating cohesively at gene loci to read DNA's instructions. Unraveling these dynamics is especially complex as most events of interest occur on length scales far smaller than the light we use to observe them. Thus from a smattering of photons of wavelength hundreds of times larger than the objects we care to characterize in biological systems, must be derived insight on life's fundamental processes. Students working on this project will quickly become experts in state-of-the-art tools of AI, simulation-based inference, Bayesian inference, and machine learning more broadly.	Programming (python or Julia)	Paid, Volunteer	[email protected]	Yes
Nicholas Matlis	Experimental	Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics	Lasers, electrons and X-rays at CXFEL	ASU hosts a ground-breaking project to build a Compact X-ray Free Electron Laser (CXFEL) whose objective is to make very short, extremely bright pulses of X-rays that allow us to peer inside matter (be it nature’s molecules or materials enabling the next generation of technology) and see its structure and dynamics at work. Two complementary machines are being built. The first is already producing first X-rays and the second is under construction. Join the team and be part of history. Projects range from developing new accelerator technologies to inventing novel ultrafast diagnostics to running experiments with lasers, electrons and X-rays. We are always looking for good people. Come by and see what fits you.	- Good with hands, ready to learn attitude, perseverance	Volunteer	[email protected]	No
Nicholas Matlis	Experimental	Cosmology, Particle, and Astrophysics, Nanoscience and Materials Physics	Extreme Beams for Future Technologies	High energy, high average-power laser systems are a versatile tool for generating exotic beams of photons and particles for exploring quantum dynamics in matter, from molecules important for life to novel materials enabling the next breakthrough in computing technologies. This research encompasses a combination of projects spanning laser development; creation of novel high-energy, highly tunable sources of terahertz-frequency electromagnetic pulses (THz pulses) using nonlinear optics; development of novel, THz-based electron acceleration and manipulation technologies, and studying the responses of matter driven into extreme regimes previously inaccessible without these specialized tools. You will get hands-on experience using and tuning laser systems, building data acquisition and control systems, transforming intense light into various other types of beams and designing and running experiments exploiting the matching of THz photon energies with key excitations in quantum materials, including spin, orbital, and lattice degrees of freedom to control material properties. Both theory and experimental projects are available.	Good with hands, ready and able to learn, able to persevere.	Volunteer	[email protected]	Yes
Chao Wang	Theoretical	Biological and Soft Matter Physics, Nanoscience and Materials Physics	Nanoscale physical analysis and modeling of gold nanoparticle distribution towards ultrasensitive protein detection	Precise detection of low-abundance proteins is crucial to early detection of a wide range of infectious and chronic diseases. Currently, this is only possible through most advanced, yet expensive and complex instrument, which are not available in resource-limited settings. To date, rapid, sensitive, and cost-effective detection on a point-of-care platform remains elusive. In this project, we aim to establish a gold nanoparticle (AuNP)-supported, rapid electronic detection (NasRED) platform with digital readout to achieve sub-femtomolar sensitivity and high specificity. Here, surface-functionalized AuNPs act as multivalent detectors to recognize target proteins (e.g. antigens, antibodies and toxins), subsequently forming aggregates precipitated in a microcentrifuge tube and producing a solution color change. Uniquely, NasRED introduces active fluidic forces through engineered centrifugation and vortex agitation, effectively promoting low-concentration protein detection and accelerating signal transduction and readout within 15 to 30 minutes. In this project, the students will work with Ph.D. students in my lab and establish physical models and simulations (for example in COMSOL or other software) to understand the complex fluidic physics/mechanics of the AuNP sedimentation and resuspension process. These studies will play an important role in future biosensor system engineering for point-of-care diagnostics of broad diseases.		Credit, Volunteer	[email protected]	Yes
Banu Ozkan	Theoretical	Biological and Soft Matter Physics	Building Physics-Integrated AI models to enhance learning in case of limited data	Proteins are the molecular workhorses of life, carrying out structural, catalytic, signaling, and regulatory roles across all living systems. Their universality and tunable properties make them powerful tools in medicine, biotechnology, and synthetic biology. However, our knowledge of protein function remains remarkably incomplete—current annotations cover only 1–10% of the known protein universe, with less than 1% of those functions experimentally verified. Most predictions rely on sequence or structural homology, yet many proteins share functional similarities without detectable sequence or structural resemblance. An emerging paradigm emphasizes protein dynamics—the patterns of motion within their conformational landscape—as a universal determinant of function. Protein motions are shaped by evolutionary pressures and correlate strongly with functional outcomes, capturing both intrinsic properties and environmental context. Recent work has introduced the concept of “MD fingerprints”: dynamic signatures derived from molecular dynamics simulations that encode how proteins explore their energy landscape. These signatures offer the potential to generalize function predictions across unrelated sequences, overcoming the limitations of purely sequence- or structure-based approaches. The major challenge lies in computational cost. All-atom molecular dynamics (MD) simulations are too expensive to apply to millions of proteins, with full coverage requiring thousands of GPU-years. Coarse-grained molecular dynamics (CG-MD) simulations offer a practical alternative, capturing essential motions at much lower computational expense. Combining these efficient sampling methods with advanced machine learning architectures such as graph neural networks (GNNs) provides an opportunity to learn dynamic–function relationships at scale. A proof-of-concept pipeline for integrating CG-MD dynamics with GNN-based function prediction, laying the groundwork for scalable annotation of uncharacterized proteins.	There will be already build codes, the student will work on to test and train the code.	Volunteer	[email protected]	Yes