This is an opportunity to learn some of the computational and bioinformatic tools used in genomics.
The project is to study the genetic basis of evolutionary adaptation using whole genome sequence data and functional genomic data (RNA-seq). The study system is a pair of coastal fish species in the genus Fundulus that inhabit a wide range of salinities. A probable chromosomal inversion exists which is shared by the two species, associated with environmental salinity and encompasses a critical osmoregulatory gene. The project will confirm the presence of the inversion and analyze genetic and gene expression data from genes it encompasses from multiple populations of each species.
The work is entirely computational in nature, as the data have already been collected. The student would be expected to learn the basics of analyzing genetic variation data, gene expression data, and identifying structural variants from whole genome sequence data.
The expected time commitment would be 10-15 hours per week. Taking the project to completion would likely require two semesters.
Applicants should have some prior experience using the linux command line interface, and ideally some experience with the statistical computing language R. Prior coursework should include genetics.
How to Apply
Please contact Noah Reid at email@example.com
Applicants should submit a resume, and explain relevant coursework and prior experience related to bioinformatics (e.g. experience using command line interfaces, scripting languages, etc).
Mentor: Noah Reid, Assistant Research Professor
Department: Molecular and Cell Biology
Timing: Spring 2019
Are you interested in accents or phonetics? Are you great with computers or music theory? This position involves assisting with research into the intonation patterns of various accents, specifically finding pitch relationships in particular speech utterances. There is also an opportunity to attend regular meetings with a faculty mentor and discuss relevant literature and research experiences in order to foster your education in the field.
This opportunity can be taken for course credit, or as a Work Study position (only for students with a federal Work-Study award), and runs in Spring Semester 2019. Students earning course credit can negotiate weekly hours (3 hours for 1 credit, 6 hours for 2 credits, 9 hours for 3 credits). Work-study students work 8-10 hours per week.
The role includes:
* Helping to recruit volunteer speakers of specific accents and request accent samples
* Assisting with recording sound samples from on-campus volunteers
* Orthographic (not phonetic) transcription of spoken samples from sound files
* Analyzing sound samples for fundamental frequency and musical interval relationships using appropriate software (e.g. Adobe Audition). Take screenshots and annotate with appropriate information. Record and organize this data.
* Assist in gathering and organizing related literature for review
* Read and summarize related literature
* Undergo online CITI Program Training Course (if required by IRB). This is online and takes less than 2 hours.
* Perform miscellaneous duties as directed
* Have excellent computer skills
* Have excellent communication skills
* Have great organizational skills and motivation
* Experience/education in any or all of phonetics, accents, linguistics, speech, music, sound engineering, computer science.
How to Apply
Please email your application to firstname.lastname@example.org and include:
* Cover Letter (please write about why you would be good at the job and why it interests you)
* References (Email or telephone numbers)
Looking to fill this position ASAP. Open until filled.
Mentor: Jennifer Scapetis-Tycer, Assistant Professor
Timing: Spring 2019
Our group specializes in molecular modeling & simulation to study biomaterials, biomechanics and biophysical processes associated with the body’s function in health and disease. We are always interested in mentoring self-motivated undergraduate students from diverse backgrounds. Multiple projects are available depending on student interest and fit.
More details on the projects can be found at: http://me.engr.uconn.edu/wp-content/uploads/2018/08/F18-REU-Anna-Tarakanova.pdf
The student will gain experience in molecular model development, atomistic modeling, coarse-graining approaches, molecular simulation setup and implementation on supercomputers, molecular visualization software, MATLAB/Python scripting, and scientific writing. The student will have a chance to participate in a collaborative project, and if successful, contribute to a scientific publication.
Research activities may include:
– Read and summarize related literature
– Build and iterate molecular models
– Perform simulations on computing cluster
– Post-process data
– Visualize and analyze data
– Meet weekly with faculty member
Commitment: 10 hours/week, including a weekly meeting with faculty member
Course credit available.
Helpful experience for all projects: Familiarity with scripting in the Linux environment, molecular modeling with molecular-dynamics-based approaches, experience with Python/MATLAB.
Preferred coursework: Differential Equations/Linear Algebra, Physics I: Mechanics/Statistical Physics, Biochemistry.
How to Apply
Interested students should email a resume/CV and a brief cover letter to email@example.com indicating why they are interested in this research opportunity. Please indicate whether you are interested in the Fall semester or both Fall & Spring.
Mentor: Anna Tarakanova, Assistant Professor
Department: Mechanical Engineering
Timing: Fall 2018, Spring 2019
Depending on previous experience and interest, students will assist with ongoing research projects including but not limited to identifying and optimizing natural and novel means of controlling pathogens in cheese. These include the use of GRAS antimicrobials (e.g. hydrogen peroxide, lauric arginate ethyl ester, polylysine, and acidified calcium sulfate), protective cultures of lactic acid bacteria, and modified atmosphere packaging to enhance the shelf life and safety of dairy products. When taken for credit (independent study/undergraduate research), time commitments can range from 3-15 hours per week. Duration can be short as a single semester or renewed for multiple semesters. Depending on the individual, the opportunity is also available during the semester breaks. This opportunity is not a paid position.
We are looking for someone with an interest in dairy science, food science, and/or microbiology.
Coursework in microbiology and/or previous lab experience are preferred.
How to Apply
Email Dr. D’Amico (firstname.lastname@example.org) explaining your interest. There is no deadline.
Mentor: Dennis D’Amico, Assistant Professor
Department: Animal Science
Patient outcomes research in clinical medicine utilizing large nationwide databases to investigate clinical questions related to liver disease and liver transplant. This is an opportunity for prospective students interested in being involved in biomedical research with the goal of learning and manipulating large medical databases. With the guidance of the mentor and statistical assistance, the prospective candidate will have the opportunity to participate in a research project in medicine. With the mentor, the student will develop a clinical question which can answered with the appropriate database, and gain experience proposing a hypothesis, working with statistical team, interpreting the results, and formulating conclusions from the results. There will be weekly meeting with the mentor and opportunity to have exposure to a clinical environment for those students interested to pursue careers in medicine. Work is primarily done independently with guidance, thus no specific number of hours per week commitment. One of the objectives of the project would be to allow the student to present his or her findings in a poster or oral presentation format at national meetings and eventual publication. This is currently a nonfunded volunteer position. The time commitment is variable depending on student’s proficency handling large databases.
Comfortable using excel database, be able to work independently, ability to perform online pubmed research to gather background literature on the topic, understand basic statistics
How to Apply
Please contact mentor directly;
Provide resume and letter of interest
Mentor: Raffi Karagozian, MD, Clinical Assistant Professor of Medicine
Department: Gastroenterology & Hepatology
Campus: UConn Health