Government
Professor Nicholas Buccola
My Brother’s Keeper is the proposed third volume in a trilogy in which I am considering the civil rights and conservative movements together. In the first volume, The Fire Is Upon Us, I considered the clashing ideas of James Baldwin and William F. Buckley Jr. – the leading writers associated with the respective movements. In the second volume, One Man’s Freedom, I considered the clashing ideas and actions of Martin Luther King Jr. and Barry Goldwater – the most prominent leaders of the respective movements. In My Brother’s Keeper, I focus leading grassroots activists associated with each movement and consider what motivated these activists and how their stories can help us make sense of our own lives as citizens. My hope is that the trilogy, taken together, will contribute to our understanding of American political history, the American present, and the possibilities for the future.
KDIS
Professor Zeynep Enkavi
In the Enkavi Lab we are interested in how people form value representations that guide their decisions and how these representations interact with other cognitive processes especially when people make bad decisions. To gain insight into these questions we use human functional magnetic resonance imaging (fMRI) data, which are whole brain recordings from alive humans while they make decisions in an MR scanner. We use these brain data to understand behavioral patterns using computational modeling and machine learning methods. Summer projects will revolve around two fMRI datasets: one on how humans learn and generalize representations of value that guide their economic choices and a second on how adolescents differ from children and adults in how they learn from negative outcomes. Students interested in working in the lab should be comfortable writing code in at least one language (preferably Python), detail-oriented, independent and a good team player. Knowledge of statistics/machine-learning is preferred but not required.
Professor Colin Rathburn
Orthogonal split luciferases for imaging multiplexed cellular behaviors
Disease progression is characterized by a complex interplay of a variety of cell types in living organisms. The ability to "see" these interactions is crucial for understanding the causes and potential treatments of illness. We are developing bioluminescent proteins that will illuminate multiple cell types at the same time in the body of a mouse to study such interactions.
Professor Nia Walker
Coral Confinement: Microbial Mysteries in Pet Stores
Corals in pet stores experience environmental conditions that differ dramatically from those in the wild, potentially altering their microbiomes and impacting their overall health and disease susceptibility. This study will investigate microbiome shifts in corals sourced from pet stores in the Claremont area. We will use 16S rRNA sequencing to characterize the bacterial and fungal communities associated with these corals, focusing on species that are common in the pet trade. In addition, we will measure key water quality parameters—such as temperature, salinity, and nutrient levels—to determine whether differences in the tank environment correlate with shifts in microbial composition. Given the frequent use of antibiotics in aquaria, we will also attempt to screen for antibiotic resistance genes to explore possible links between captivity, microbiome alterations, and antimicrobial resistance.
This research project aims to provide insights into how captive conditions affect coral microbiomes, with broader implications for marine conservation and pet trade management. Understanding these microbial shifts could inform strategies to improve coral health and reduce disease risks in captive populations. The project will involve field sampling in local pet stores, molecular techniques (including DNA extraction, PCR, and sequencing), data analysis, and scientific writing. Prior experience in molecular biology or having completed SCI 10 are beneficial, but students from any major at CMC are welcome to apply. There are up to three available positions.
Mathematical Sciences
Professor Evan Rosenman
When evaluating the efficacy of a health intervention, researchers often have access to two types of data: observational data from sources such as electronic health records databases, and experimental data from randomized trials. Observational data are often large and representative, but individuals who receive the intervention differ from those who do not, making causal estimation difficult. In contrast, experimental data use random treatment assignment to facilitate causal estimation, but experiments are often costly to conduct. This project focuses on how to combine these two types of evidence. We will primarily use methods from Empirical Bayes, a toolkit for flexibly combining and weighting estimators. We will focus on questions like how to estimate average treatment effects; how to synthesize dose-response curves across datasets; and how to narrow confidence intervals for subpopulation causal effect estimates using observational data. Methods will be tested on two real-world datasets: the Women’s Health Initiative, which studies hormone therapy, and a database linking air quality to Medicare claims.
Interested students should have taken Math 151 and ideally Math 152 and should be comfortable with common statistical concepts like point estimators, confidence intervals, and Maximum Likelihood. Students should also be comfortable with statistical programming in R.
Professor Mark Huber
A graph (also known as a network) is a collection of nodes, some of which can be connected by edges. Suppose the nodes are each assigned a color from a fixed set. The coloring is *proper* if no two nodes connected by an edge are given the same color. Let Delta be the largest number of nodes any particular node is connected to. If the number of colors is greater than Delta, then you are guaranteed that a coloring exists. The question I'm interested in is: given a graph, is it possible to choose uniformly at random from the set of proper colorings of the graph? A fast algorithm for doing so would enable the approximation of the number of colorings of the graph, which is a number-P complete problem. (These number-P complete problems are harder than NP complete problems for comparison.) The goal will be to develop an algorithm that provably runs in linear time when the number of colors is at least a constant times Delta.
Philosophy
Professor Amy Kind
I invite applications from students with a background in philosophy (minimally two college-level courses) who are interested in working on a project on “Desire, Fiction, and Fantasy.” When engaging with fiction, we have all sorts of desires about the characters and events that we are imagining. But when we have these desires in imagination, what do they say about us and our character? And what about the desires we have in the course of fantasizing? Should we be held morally responsible for our fantasy desires, even if we don’t ever intend to act on them? I would benefit from the assistance of two or three students as I work on this project. The student team will assist with background research, including compiling an annotated bibliography, and each student will be expected to write a short paper of their own. The research team will meet on a weekly or bi-weekly basis. I welcome applications from individual students or students who would like to apply as part of a group. I am also open to student-designed projects on other topics relating to fiction, fantasy, or imagination. Students interested in working with me are strongly encouraged to come talk with me prior to submitting an application.
Professor Rima Basu
I am happy to supervise any projects that fit into the following broad themes: (1) the moral challenges of assimilation and cultural conflict, (2) the nature of curiosity and the moral limits on curiosity, in particular, with relation to how we conduct both scientific inquiry and interpersonal inquiry, e.g., our beliefs about one another (3) the moral and epistemic challenges of what we choose to remember and what we choose to forget, in particular, how this pertains to war photography and the documentation of horrific events without that documentation devolving into spectacle or voyeurism. Interested students should have some background in philosophy (minimally two courses) and will be expected to produce writing on a weekly basis (be it their own research or summaries of things they have read).
Psychological Sciences
Professor Gabriel Cook
Directed by Professor Cook, the Cognition and Data Visualization Laboratory is seeking research assistants to collaborate on multiple research projects described below.
A focus of the Cognition and Data Visualization Laboratory is to understand how people attend to, perceive, remember, and make decisions using data visualizations. In particular, this project is focused on examining and understanding measures of graphical literacy. The project involves reading and discussing the relevant literature on data visualization, either learning to clean or manipulate data with R or reinforcing existing skills, and creating stimuli. This project is ideal for students interested in psychology, cognitive science, data science, or visualization who are passionate about understanding how people interact with data visualizations and want to contribute to the development of more effective and unbiased visualizations. Applicants should be detail-oriented and be able to work both collaboratively and independently.
The Cognition and Data Visualization Laboratory is seeking research assistants to help apply large language models to evaluate features of written text and classify those text. We will explore how features extracted from these models can inform our understanding on human cognition. As a research assistant, you will explore relevant work, work with APIs, implement and fine-tune language models using Python, analyze data, and summarize findings. Familiarity with lexicon-based and large language models (e.g., BERT, RoBERTa, LLaMa) is advantageous but is not required. Basic programming skills in Python are necessary. Students interested in psychological science, data science, computer science, and linguistics who want to apply language models to real-world problems are encouraged to apply.
Professor Stacey Doan
Directed by Dr. Stacey Doan, the Applied Mind and Health Laboratory, the research arm of the Berger Institute, is seeking research assistants to work on multiple research projects funded by the National Institutes of Health, the National Science Foundation, and the Ho Family Foundation. Research projects in our lab take an interdisciplinary approach to examining how biological, psychological, and social factors interact to predict health and well-being. Some topics we hope to pursue this summer include the role of relationships and belonging on health, sleep in college students, racial-ethnic discrimination, and neighborhood effects. Research assistants are encouraged to take a team-based approach to develop and pursue their own research questions with our data. Research assistants will be trained in all aspects of social-behavioral research methodology, including hypothesis generation, data collection, data analysis, and manuscript preparation. The position is a particularly good fit for those interested in graduate school in psychology, neuroscience, or medicine.
Professor Jennifer Feitosa
Research opportunities are available to study diverse teams in the workplace under the supervision of Prof. Jenn Feitosa at the METRICS Lab. METRICS Lab stands for the Methodological Examination of Teams Research in Inter-Cultural Settings. Current summer projects will explore topics such as virtual teams, equity measurement, homophily, family-building friendly workplace, and belonging abroad. We are looking for responsible, motivated, and hard-working individuals. Research assistants will engage in various aspects of the research process, including literature search, data collection, data analysis, and/or manuscript preparation. These opportunities provide valuable experience for those interested in graduate studies or careers in organizational psychology, business, or related fields.
Professor Sharda Umanath
The Umanath Memory and Aging Laboratory will be working on a project related to the nature of knowledge and its influence on remembering. It focuses on understanding retrieval failures – when we try to remember something and we can’t bring it to mind – and investigating what strategies are most effective for recovering that information in our memories. This summer, students will work with older adult community members (recruit participants and collect data) as well as working on analyzing data. The project will also involve reading the relevant literature with opportunities to work on scientific writing. Preference will be given to students who have research experience, have taken Cognitive Psychology and/or Research Methods, and are interested in working with older adults.