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Opportunities Database

Faculty, Post-Docs, and Graduate Students: Click here to post a research opportunity.

NOTE: If you are eligible for Federal Work-Study (FWS), you can find hundreds of research opportunities on the FWS website. To find out if you are eligible or if you are new to having a FWS award, visit the UNC FWS website. If you are a returning student who already completed the mandatory training and has access to JobX, log in and click “Find a Job” under the student menu. From there, click the “Research Jobs” button in the middle of the page.

Students with or without FWS can use the database below to look for opportunities.


Volunteer Undergraduate Research Assistant

Suggested Fields
Post Date
06/19/2024
Description

Seeking highly motivated students to start Summer Session II, with the possibility to continue during Fall 2024. Dr. Sheeran’s laboratory is exploring the comparative prevalence of observational and experimental studies in health psychology journals.

Explicitly, we seek to answer the following questions: Are observational studies more likely to be (a) conducted and (b) cited than intervention studies in health psychology? Is there a self-fulfilling prophecy?
Undergraduate Research Assistants involved in this study will have the chance to contribute to different aspects of the research, such as searching for articles within the SCOPUS database and inputting/organizing data in Excel files. Students in this position should be available for a minimum of 8 hours/week. If you’re considering graduate school, this is a great opportunity to experience working on a research study. We strongly encourage applications from diverse backgrounds. If interested, please email your resume to Yifei Pei (yifeipei@email.unc.edu).

Faculty Advisor
Dr. Paschal Sheeran
Research Supervisor
Yifei Pei
Faculty Email:
Type of Position
Availability
Post End Date
07/31/2024

Research Assistant

Post Date
06/04/2024
Description

The Frohlich lab is seeking highly motivated undergraduate students to join our team as Research Assistants (RAs). Our lab is dedicated to understanding the neural basis of behaviour and developing novel treatments for psychiatric and neurological disorders through the interdisciplinary study of network dynamics. We integrate preclinical and clinical research using electrophysiology, imaging, brain stimulation, cognitive assays, and clinical trials methodology. RAs will assist in various research activities within the cognitive/pre-clinical arm under Dr. Agnieszka Zuberer or the clinical arm under Dr. Flavio Frohlich. Our work is supported by advanced data analysis, computational modelling, and machine learning, all in close conjunction with our experimental efforts.

We expect our RAs to commit to 60 hours per month. Candidates should have a minimum GPA of 3.5. We also value candidates who have participated in extra-curricular activities. As an RA, you will be involved in data collection, analysis, and interpretation, aiding in the preparation of research presentations and publications, participating in lab meetings, and contributing to ongoing projects. The Frohlich lab fosters a learn-as-you-go approach, encouraging RAs to develop their scientific skills throughout their tenure.

Responsibilities include participating in data collection, analysis, and interpretation, supporting the preparation of research presentations and publications, engaging in lab meetings, and contributing to ongoing projects. The environment at the Frohlich lab supports a learn-as you go approach, and candidates are encouraged to develop their scientific skills throughout their tenure as an RA. We have a track record of RAs being accepted into either medical school or graduate school after working with us. We attribute this to the high level of mentorship support being offered to RAs from the rest of the research team.

Ideal candidates will have a strong academic record, a keen interest in cognitive neuroscience and psychiatry/psychology, particularly in the areas of major depressive disorder and anxiety disorders, and strong organizational and communication skills. This position offers the opportunity to gain hands-on research experience in a cutting-edge lab, work closely with a team of experienced researchers, develop skills in data collection, analysis, and scientific writing, and enhance academic and professional development in the field of neuroscience and psychiatry.

Interested candidates are invited to submit a current resume/CV, a cover letter detailing their interest in the position and any relevant experience, and an unofficial transcript. Please send your application to Max Archibald Montgomery at montgom@email.unc.edu. We are excited for you to join us in making a difference in the field of psychiatric research!

Faculty Advisor
Flavio Frohlich
Research Supervisor
Max Archibald Montgomery
Faculty Email:
Type of Position
Availability
Post End Date
06/30/2024

Research assistant

Post Date
06/04/2024
Description

The cognitive arm of the Frohlich lab, led by Dr. Agnieszka Zuberer, is actively seeking highly motivated undergraduate students to join our cognitive research team as Research Assistants (RAs). Our lab specializes in the study of emotion through the use of emotionally evocative movie clips, employing pupillometry and subjective annotations as outcome measures. We are committed to understanding the neural basis of behaviour and advancing treatments for neurocognitive disorders by exploring network dynamics. Our cognitive arm utilizes advanced tools such as EEG, fMRI, and TACS to delve into brain function, supported by sophisticated data analysis, computational modelling, and machine learning techniques.

We expect our RAs to commit to 60 hours per month. Candidates should have a minimum GPA of 3.5. We also value candidates who have participated in extra-curricular activities. As an RA, you will be involved in data collection, analysis, and interpretation, aiding in the preparation of research presentations and publications, participating in lab meetings, and contributing to ongoing projects. The Frohlich lab fosters a learn-as-you-go approach, encouraging RAs to develop their scientific skills throughout their tenure.

Ideal candidates will possess a strong academic record, a keen interest in cognitive neuroscience and psychiatry/psychology, particularly in areas related to major depressive disorder and anxiety disorders and exhibit strong organizational and communication skills. This position offers a unique opportunity to gain valuable research experience, work alongside experienced researchers and clinicians, and enhance your academic and professional development in neuroscience and psychiatry.

To apply, please submit a current resume/CV, a cover letter detailing your interest in the cognitive research arm, and an unofficial transcript to Max Archibald Montgomery at montgom@email.unc.edu. We look forward to reading your application!

Faculty Advisor
Agnieszka Zuberer
Research Supervisor
Max Archibald Montgomery
Faculty Email:
Type of Position
Availability
Post End Date
06/30/2024

Undergraduate RA Positions in the Penn Lab (Social Cognition and Psychosocial Treatment for Schizophrenia)

Suggested Fields
Post Date
05/22/2024
Description

The Penn Lab is hiring undergraduate research assistants to begin in Summer 2024, with opportunities to continue on in the coming academic year. The Penn Lab primarily works with individuals who have experienced their first episode of psychosis (FEP) or who have a schizophrenia spectrum disorder (schizophrenia, schizoaffective disorder, or schizophreniform). Dr. David Penn’s research typically focuses within two areas: social cognition and psychosocial treatment for schizophrenia.

Some current studies include:

The Horyzons Project: Horyzons is a moderated online social therapeutic (MOST) platform adapted for Americans with schizophrenia spectrum disorders and first episode psychosis (FEP). This platform was built much like a social media platform but has additional features central to mental health and recovery (such as access to online therapists, peer support specialists, and wellness activities based in psychoeducation and cognitive behavioral therapy). Previous Horyzons implementation within clinical services assessed the effectiveness of the platform in the recovery of individuals experiencing FEP. The current Horyzons project assesses the implementation and integration of the digital intervention within specialized FEP standard care.

The Altitudes Project: Altitudes is a digital platform for families with loved ones experiencing schizophrenia spectrum disorders and FEP. The platform, originally developed for Australian families, is being adapted for American families and contexts. The platform provides psychoeducation, skills, online therapists, and family peer specialists to support themselves and their loved one in the journey to recovery. Altitudes is currently being piloted with family members from two specialized FEP clinics. The project will assess the effectiveness of the platform in improving and supporting caregiver mental health and social facets.

Previous studies still in data analysis include:

PACE-Life: Physical Activity Can Enhance Life. This study is currently in the randomized control trial phase and data collection has now been completed. Participants with schizophrenia spectrum disorders or unspecified psychosis were randomly assigned to either Fitbit only or Fitbit + the PACE-Life exercise intervention. During the pandemic, this intervention involved virtual exercise groups held for participants twice a week.

Targeting Stress Reactivity in Schizophrenia: Integrating Coping Awareness Therapy (I-CAT): The purpose of this study was to develop and then subsequently evaluate a mindfulness and positive therapy intervention for individuals with first episode psychosis. Following a manual development period, an open trial of six clients was conducted, which led to a small-scale RCT (n=40). The study was completed in January 2020, and we are currently in the data analysis phase of this trial.

Race and Psychosis Intervention Development (RAPID): This project aimed to develop a culturally tailored treatment for Black Americans with first-episode psychosis (FEP). This project was completed in two phases. The first phase (recently completed) involved qualitative interviewing of clients, family members, clinicians, and PS/S and SE/E specialists with experiences in dealing with FEP. These interviews will inform the development of a culturally tailored treatment manual.

Responsibilities in this position may include (though not limited to):
● Querying and organization of data about participant engagement with a digital intervention for first episode psychosis;
● Transcription of audio/video files from qualitative interview recordings;
● Qualitative analysis of transcriptions, including possible codebook creation or other reporting;
● Administering questionnaires to participants

Please submit your application to the Penn Lab here (please do not submit through Office of Undergraduate Research): https://forms.gle/XKKeG9sK4jfg83887

Faculty Advisor
David Penn, PhD; Kelsey Ludwig, PhD
Research Supervisor
Bryan Stiles, MA
Faculty Email:
Type of Position
Availability
Website
Post End Date
06/22/2024

Neurology Research Assistant (School of Medicine)

Post Date
05/17/2024
Description
About our Clinical Research Lab: UNC’s rs-fMRI Clinical Service and Neuroscience Research Lab is a multidisciplinary group here at UNC’s School of Medicine in the Department of Neurology, led by Dr. Varina Boerwinkle; Director and Division Chief of Pediatric Neurology. We focus on both clinical care and research, where many of our projects look at understanding neurological disorders such as epilepsy, coma, and traumatic brain injuries through the lens of resting state fMRI
Neurology Research Assistant Position: Because of the diverse nature of neuroimaging and clinical neurology, we are always interested in working with students who are studying biological sciences as well as computer science, statistics, and mathematics. Typical duties of our research assistants include retrospective data collection, generating whole brain maps of retrospective patients, investigating electronic health records, conducting literature reviews, and assisting other team members with various day to day lab activities. Additionally, we encourage and support our lab members to present their findings, both locally on campus as well as nationally in conferences. This may take the form of poster presentations, journal publications, or others events.
Ideal Candidates: Seeing whether you are a good fit for this lab is just as important as seeing whether this lab is a good fit for you. The skills and experience you will gain by working with us may include any or all of the following, depending on your interests: Neuroanatomy, epilepsy, neurology, MRI/fMRI, diagnostic imaging, scripting and programming, data analysis, scientific methods, and bioinformatics/health data. The most important traits we look for are work ethic, availability, and being proactive. Having prior research experience is always helpful, but not mandatory.
How To Get Started: Please send an email to Will Reuther, our manager (william_reuther@med.unc.edu) introducing yourself, what you are studying, what your future career goals are, and any relevant research or work experience you may have. Please feel free to reach out with any questions. We look forward to hearing from you!
Faculty Advisor
Varina Boerwinkle
Research Supervisor
William Reuther
Type of Position
Availability
Post End Date
08/19/2024

Undergraduate research assistant: Artificial neural network (Deep learning, AI) for computational systems neuroscience

Post Date
05/01/2024
Description

[Research description==Qualifications]
– Goal: Document & refactor code for simple & flexible ANN experiments (Engineering & Science)
– Time commitment: 6+ hours/week
– Date & duration: Starting August 2024 for 1+ years
– Language: python (pytorch, numpy, pandas, sklearn, etc)
– Work style: Transparent & Concise
– Course of research:
1. Code library literature review
2. Code reading + documentation (Graphic & written)
3. Refactor code bases

[You get]
– Amazing end-to-end technical & conceptual skills for Science & Machine learning
– Practical technical skills: python virtual environment, adjusting computing platforms, IDE, git, python libraries (pytorch, numpy, pandas, sklearn, etc), drawing figures, presentation skills
– Conceptual skills: concise coding, computer architecture, ANN, machine learning research pipeline, computational neuroscience
– Supervisor acknowledged as the best coder throughout past labs
– Recommendation letter
– (Long horizon, 1+ year) Paper publication

[To apply]
Please fill out the following google form: https://docs.google.com/forms/d/e/1FAIpQLSfdKZyD2KxAAyXczqZuSrC03Gied9qHFt-NxCUTDiRR1zTbgA/viewform?usp=sf_link
We’ll keep this form open during summer and reach out for interviews late July-Early August.

[More information]
Hantman Lab: https://www.med.unc.edu/neuroscience/hantmanlab/
Jaesung Yoo: https://jaesung.tech.blog/

Faculty Advisor
Adam Hantman
Research Supervisor
Jaesung Yoo
Faculty Email:
Type of Position
Availability
Website
Post End Date
08/18/2024

Undergraduate Research Assistant Opportunities at (MURGE Lab) on Large Language Model Reasoning/Uncertainty/Multi-agent Interactions/Multimodality

Post Date
04/12/2024
Description

Advisor: Prof. Mohit Bansal (https://www.cs.unc.edu/~mbansal/)
Mentor: Elias Stengel-Eskin (https://esteng.github.io)
Group: Murge Lab UNC-CH (https://murgelab.cs.unc.edu/)
Duration (Flexible): Apr 15th – Sep 15th, 2024 (5 months), at least 20 hours per week commitment.
Role: Research Assistant (with RAship stipend)
Contact: Elias Stengel-Eskin (esteng@cs.unc.edu) with some basic information about yourself, your transcripts, your CV, and any discussion about any prior Machine Learning / Programming experience you have.

Requirements from Candidates (Good to Haves):
– Undergrads or Masters students from Computer Science, Mathematics/Statistics, or Linguistics/Cognitive Science background.
– Strong foundation in machine learning and deep learning techniques. Familiarity with model architectures like transformers, etc.
– Familiarity with deep learning programming frameworks like Pytorch and Huggingface libraries.
– Preferred: experience with code generation (semantic parsing, text-to-code) or vision-language tasks.
– Strong analytical abilities to ask the right questions to come up with a hypothesis and then design experiments to test it.
– Candidates who are possibly interested in a research career or grad school (Master/PhD) or Machine Learning jobs in the future.

Project Description:

Large language models allow people to interact with digital systems using natural language. However, language is inherently ambiguous and underspecified, and can lead to high uncertainty. This project will focus on enabling safe and robust interactions that allow people to make informed choices on when to trust model outputs. Core topics include: how to better model uncertainty, how to leverage multiple models to address ambiguity, how to intelligently obtain information to reduce uncertainty, and how to produce outputs that help users form their own uncertainty estimates. Topics may also include: multimodality and multimodal generation, vision-language tasks.

Research Areas:
– Multi-agent interactions and collaboration.
– Acquiring information for uncertainty reduction.
– Calibration and confidence estimation in LLM reasoning.
– Attributable and interpretable text generation.
– Multimodal reasoning and generation.

Some recent and representative papers in the direction:
1. Rephrase, Augment, Reason: Visual Grounding of Questions for Vision-Language Models, ICLR 2024 (https://arxiv.org/abs/2310.05861)
2. ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs (https://arxiv.org/pdf/2309.13007)
3. MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models (https://arxiv.org/abs/2402.01620)
4. Soft Self-Consistency Improves Language Model Agents (https://arxiv.org/abs/2402.13212)
5. Contrastive Region Guidance: Improving Grounding in Vision-Language Models without Training (https://arxiv.org/abs/2403.02325)
6. Did You Mean…? Confidence-based Trade-offs in Semantic Parsing, EMNLP 2023 (https://arxiv.org/abs/2303.16857)
7. Zero and Few-shot Semantic Parsing with Ambiguous Inputs, ICLR 2024 (https://arxiv.org/abs/2306.00824)
8. ReGAL: Refactoring Programs to Discover Generalizable Abstractions (https://arxiv.org/abs/2401.16467)
9. GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations (https://arxiv.org/abs/2402.12348)
10. VideoDirectorGPT: Consistent Multi-scene Video Generation via LLM-Guided Planning (https://arxiv.org/abs/2309.15091)
11. Any-to-Any Generation via Composable Diffusion (https://arxiv.org/abs/2305.11846)

For inquiries or to express your interest, please send an email to esteng@cs.unc.edu

Faculty Advisor
Mohit Bansal
Research Supervisor
Elias Stengel-Eskin
Faculty Email:
Type of Position
Availability
Website
Post End Date
08/15/2024

Undergraduate Research Assistant

Post Date
01/25/2024
Description

Dr. Can Chen, a faculty member of the School of Data Science and Society, is seeking undergraduate research assistants to join his research team in the field of data science. The research focuses on developing and applying artificial intelligence and dynamical systems techniques to solve problems in the field of data science. Dr. Chen’s research interests span a diverse range of fields, including control theory, network science, tensor algebra, numerical analysis, data science, machine learning, deep learning, hypergraph learning, data analysis, and computational biology.

Faculty Advisor
Can Chen
Research Supervisor
Can Chen
Faculty Email:
Type of Position
Availability
Post End Date
06/30/2024

Hydrodynamic Quantum Analogs with Walking Droplets

Post Date
01/05/2024
Description

The Physical Mathematics Lab (PML) (Intro Video) offers a wide range of interdisciplinary problems that find motivation in very diverse fields, including soft matter, fluid mechanics, biophysics and quantum mechanics. One of PML’s themes is the study of new Hydrodynamic Quantum Analogs (HQAs) with walking drops (Video). Millimetric liquid drops can walk across the surface of a vibrating fluid bath, self-propelled through a resonant interaction with their own guiding or ‘pilot’ wave fields. These walking drops exhibit features previously thought to be exclusive to the quantum realm. This system has attracted a great deal of attention as it constitutes the first known and directly observable pilot-wave system of the form proposed by de Broglie in 1926 as a rational, realist alternative to the Copenhagen Interpretation (Video & Read). At PML, we work to unveil and rationalize new HQAs, thus challenging the limits between the quantum & classical worlds. Our investigations blend experiments & mathematical modeling (theory & simulations), we can thus tailor your project according to your interests & skills. Prior research experience is not necessary, you just need to be eager to learn!

Faculty Advisor
Pedro Saenz
Research Supervisor
Pedro Saenz
Faculty Email:
Type of Position
Availability
Website
Post End Date
06/30/2024

Examining Mechanisms Underlying Performance Fatigability in Women

Suggested Fields
Post Date
11/14/2023
Description

The Motion Science Institute is currently recruiting healthy women between the ages of 18-30 to participate in a research study examining performance fatigability in women. Participants must have a BMI of ≥ 30 kg/m2 and not currently be on hormonal contraception.

Participants will receive free body composition analysis and $50 for taking part in this study.

If you are interested, please visit our website or contact Amber Schmitz by email at amberns@unc.edu.

Faculty Advisor
Dr. Eric Ryan
Research Supervisor
Amber Schmitz
Faculty Email:
Type of Position
Availability
Website
Post End Date
05/09/2024