Sort by
Refine Your Search
-
Posting Open Date Posting Close Date Qualifications Minimum Education and Experience The candidate should hold a PhD degree in Computer Science, Information Systems, Computer Engineering, or a related field
-
Qualifications Experience in quantitative modeling, stock assessment, population dynamics, statistics, and computer programming (R, Python, Matlab, Template Model Builder, AD Model Builder) are preferred
-
Qualifications Experience in quantitative modeling, stock assessment, population dynamics, statistics, and computer programming (R, Python, Matlab, Template Model Builder, AD Model Builder) are preferred
-
research laboratory, excellent communication skills, excellent computer literacy. This research over a large span of life science topics and technical approaches, including genetics, biochemistry, cell
-
experience in a research laboratory, excellent communication skills, excellent computer literacy. This research over a large span of life science topics and technical approaches, including genetics
-
such as Medicare, Medicaid, or commercial insurance databases and/or electronic health record databases in a research setting. Knowledge in pharmacoepidemiological research methods and programming skills
-
duties. Must be computer literate with proficiency and working knowledge of database and reporting tools such as Microsoft Word, Excel, and PowerPoint. Must have the ability to work collaboratively and
-
current, past and planned future research, a teaching statement if intending to teach, and the names/e-mail addresses of three references. Please note references will receive an email to upload letters
-
current, past and planned future research, a teaching statement if intending to teach, and the names/e-mail addresses of three references. Please note references will receive an email to upload letters
-
, or Ph.D. expected by May 2026. Experience: Demonstrated experience in at least one of the following areas: -Methodology development in wavefunction-based electronic structure methods, quantum Monte