Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
the following areas: Performing and/or analyzing functional genomics experiments Competence with Unix environment, R, Python, high performing cluster Familiarity with machine learning Have taken coursework in
-
, engineering, or chemistry prior to the start date. Please email Prof. Lee R. Liu at leeliu@purdue.edu with your CV, contact information for 2-3 references, and a brief research statement outlining your
-
analysis. Experience with Python and/or R; familiarity with deep learning frameworks is a plus. Demonstrated record of research productivity (publications, conference presentations). Excellent communication
-
word processing, data management, powerpoint, and some combination of (SPSS, SAS, R, and NVIVo). What is helpful: PhD preferred. What We Would Like you to Know : Purdue University will not sponsor
-
of experience in fabrication, assembly, or testing of mechanical or electromechanical systems (experience in R&D or prototype environments preferred) Experience with CAD design tools (e.g., SolidWorks, Autodesk
-
with packages like SPSS, SAS, or R for advanced analysis. Data visualization/Business Intelligence (BI) tools: Experience with tools like Tableau, Microsoft Power BI, or similar to create dashboards and
-
multidisciplinary research environments or R&D settings Multiple years of experience in digital manufacturing, computational modeling, or AI/ML applications in engineering Skills Needed: Proficiency in modeling and
-
undergraduate student Excellent research, analytical, and writing skills Experience or Familiarity with Python or R Ability to work independently and as part of a team Preferred Qualifications Strong interest
-
judged from published papers or publicly available (e.g., arXived) preprints, will be given priority. Strong programming skills in R/Python/MATLAB with some knowledge of C/C++ will be preferred. Prior
-
Pharmacoepidemiology, Health Services Research, Public Health, Biostatistics, or a related discipline Demonstrated commitment to addressing health disparities Strong quantitative skills (e.g., SAS, R, STATA) Excellent