Research Opportunities Database
|Title||Number of opportunities||Posted||Last Updated|
|Combatting "superbugs" by reducing unnecessary antibiotic use||
Assist with data collection and analysis for studies of doctor-patient interaction and antibiotic stewardship interventions at University Health Service. 6-15 hours/week, credit or paid work both available.
Mentor: Erina MacGeorge
|6||August 16, 2018||August 16, 2018|
I mainly study massive star winds that are driven by radiation. However, it involves significant amount of numerical computation, visualization and analysis of data. However, I am seeking student involvements in a wide range of other topics that require numerical computations/computer modeling. For example, supernovae, accretion disks, solar winds, planetary magnetospheres (like Jupiter) etc. I have experience with a number of different astrophysical numerical codes such as Zeus-MP, FLASH, PLUTO, AMRVAC. Most of them use Fortran, but PLUTO uses C programming language. These codes are very versatile and I will be happy to guide any interested student in learning and applying these tools. An ideal student will be familiar with Unix/Linux type of computer operating system, know scientific programming language (Fortran, C, C++), or other script languages (Perl, Python etc). Having a strong calculus background will also be helpful.
Mentor: Asif ud-Doula
|1-4||January 1, 2018||July 24, 2018|
|Computational biology for understanding gene regulation||
New experimental approaches based on DNA sequencing are allowing us to see where various gene regulatory processes are happening along the genome. However, these experiments produce vast amounts of data, and so turning them into an understanding of the regulatory circuitry controlling cells remains a huge challenge. The Mahony lab aims to meet this challenge by developing machine learning algorithms for detecting patterns in large regulatory genomics datasets. In particular, we focus on understanding how transcription factors and other regulatory proteins control cell behavior during development and cellular programming. We need motivated undergraduate students to help us to analyze regulatory genomics datasets and to help develop bioinformatics tools for data mining and visualizing large collections of genomics data.
Mentor: Shaun Mahony
|2||January 1, 2018||July 24, 2018|
|Computational Tools for Real-Time Science||
We are bringing online a new behavioral science lab applying technological solutions to answer questions in the behavioral sciences. I'm interested in students with programming skills who are interested in building and applying tools for face- and gesture-tracking, computer-generated avatars, virtual reality, wearable technology (like Fitbits and Pebble watches) to try to understand the way people act in everyday life, and to intervene to help them be better.
Mentor: Timothy Brick
|2||January 1, 2018||July 24, 2018|
|Consumer interest in organic, GMO and related foods; Food marketing channels; Food advertising strategy and regulations||
1. data analysis and fieldwork on consumer perceptions of non-traditional foods
Mentor: Julie Stanton
|unset number||January 1, 2018||July 24, 2018|
|Context and Development Lab (CDL) – Undergraduate Research Assistant||
Description of Research: Research interests in the lab involve understanding how context shapes adolescents' development and how race, ethnicity, and other cultural attributes interact with contextual characteristics to influence adolescent outcomes. Past projects in the lab (FAN-C: Families, Adolescents, and Neighborhoods in Context; PLACES/LUGARES) have explored the roles of different contexts such as residential neighborhood, school, family, etc. on African American and Latino adolescent's academic outcomes as well as other beliefs (e.g., educational attainment and cultural values and behaviors (e.g., deviance, substance use). Our current projects are ENLACES/TIES, a collaborative project with Dr. Mayra Bamaca designed to explore family, peer, and neighborhood influences on youth behaviors, as well as a qualitative data analysis project analyzing parent and youth focus groups for major themes related to parenting and neighborhood and race/ethnicity-related experiences.
Opportunities for undergraduates in this lab include assisting with data collection (e.g., preparing research materials, interacting with adolescents, entering and coding data) and analysis (e.g., running descriptive statistics and simple analyses, preparing data manuals, conducting literature searches, and completing annotated bibliographies). Students are also trained in working with qualitative data - a unique experience in the Psychology department at Penn State! Other lab tasks may be assigned as needed. Publication and honors thesis research possibilities exist.
Method of Compensation: Research assistants may apply for PSY 494 or HDFS 496 course credit or work on a volunteer basis. Participation provides valuable experience, training in important research-related skills, and a reference base for those considering graduate studies.
Requirements/Qualifications: Because of the nature and training involved with the study, we ask for a minimum overall GPA of 3.3 and a minimum commitment of at least 2 semesters. Students are required to spend 10 hours per week involved in lab-related activities, including a 1.5 hour weekly lab/coding meeting which research assistants are required to attend.
Bilingualism (i.e., Spanish) is strongly desired but not required.
Summer opportunities are available.
If you are interested in becoming a member of the Context and Development lab, please complete the Undergraduate Research Application (available online: http://labs.la.psu.edu/contextlab/students.shtml) and email it to Dr. Witherspoon, firstname.lastname@example.org OR email@example.com, with the subject: Context and Development Lab Undergraduate RA application.
Mentor: Dawn Witherspoon
|10||July 16, 2018||July 24, 2018|
|CurtisLab, Engineering & Life Sciences||
CurtisLab of the Department of Chemical Engineering has a diverse array of ongoing projects that are generally quite applied and focus on realizing low-cost mechanisms to scale-up processes. A key benefit of CurtisLab is its highly interdisciplinary nature, which enables vicarious learning and a holistic approach to problem-solving and research. The processes are varied and range in focus across disciplines including:
CurtisLab heavily relies on undergraduate researchers to pursue high-risk (but high reward!!) research, encouraging them to adopt a mindset of 'fast failure' initially towards later-stage (nearly) autonomous experimentation. Over 50 honors theses have been completed in CurtisLab with many (equally-talented and dedicated) non-honors students contributing to research including (first) authorship on papers, winning poster competitions at National competitions, award of NSF graduate student fellowships, etc. With more than 400 undergraduates having worked in CurtisLab in the last 28+ years, CurtisLab alumni are throughout industry--anywhere from small startup companies (lots of biotech) to Big Ag / Big Oil / Big Pharma--and can provide a valuable network throughout one's post-baccalaureate career.
Projects anticipated to be active in the 2017-18 academic year include the following:
If you are interested in any of the above projects, please apply through http://www.curtislab.org/about/interest. More information is also available at http://www.curtislab.org/research-projects. No previous experience is required; work ethic, aptitude for steep learning curve, intensity, and excitement for exploration / dealing with uncertainty are highly-valued.
Mentor: Wayne Curtis
|undefined||January 1, 2018||July 24, 2018|
|Data entry and analysis from Grand Teton National Park Visitor Use Study||
Selected students will have the opportunity to help with data entry and analyses from park-based visitor use management projects. The focus of this experience will be working on social science data from Grand Teton National Park.
Mentor: Derrick Taff
|3||September 4, 2018||September 4, 2018|
Recurrent deep learning methods are changing what we can do in artificial intelligence. We are exploring problems in text, coding, and sequence understanding.
Mentor: C Lee Giles
|TBD||January 1, 2018||July 24, 2018|
|Desgining and buliding an open source telescope||
This project is focused on building an Ultrascope Explorer (an open source telescope) using 3D printing and laser cutting technologies, extending its capabilities by adding new features and ultimately designing and building a different size (bigger) telescope with remote access and control capabilities. This is a unique multidisciplinary research project that includes collaboration between faculty from engineering, IST, Physics (astronomy), and a group of engineering students. The research aspects of the project include engineering design, 3D printing/production, software and hardware design, and teamwork.
Mentor: Asad Azemi
|2||January 1, 2018||July 24, 2018|