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Job ID: 202266

Senior Research Assistant - Computational Modeling, Drug Discovery
Tufts University

Date Posted Dec. 21, 2022
Title Senior Research Assistant - Computational Modeling, Drug Discovery
University Tufts University
Medford, MA, United States
Application Deadline Open until filled
Position Start Date Available immediately
  • Professional Staff
  • Research/Technical/Laboratory


This is a grant funded position and is not eligible for severance pay.


The faculty in MBM are united by a common interest in the biology of microbes (bacteria, fungi, viruses, and parasites) and the effects of microbes on human and animal hosts. The microbial pathogens program studies microorganisms that cause infectious diseases, with emphasis on rigorous analysis of these pathogens and the immune responses that restrict them.


Program investigators direct detailed studies of pathogenic bacteria, viruses, fungi and eukaryotic parasites. Research topics include structural analysis of virus entry, viral evolution, viral oncogenes, intracellular bacterial pathogens, microorganisms that cause diarrhea and pneumonia, intracellular signaling, pathogen adhesion, genetic determinants involved in susceptibility to infection, vaccine development, and identification of novel antimicrobial agents.


What You'll Do

The Senior Research Assistant responsibilities include:

  • Plans, organizes, and conducts highly independent research project(s), including designing, testing, and evaluating methodologies and protocols
  • Analyzes and organizes data and data collection systems, interprets and summarizes results, and writes materials for publication and presentation
  • Manages laboratory analysis operations, including oversight of coding practices, mathematical modeling, and rigor of analysis
  • Trains and supervises laboratory staff and evaluates work


What We're Looking For

Basic Requirements:

  • Knowledge and skills typically acquired by a Master's degree engineering, math, or science
  • Minimum of 5 years of progressively responsible experience in a related field of research

Preferred Qualifications:

  • Experience managing and directing advanced applied analysis techniques to complex data

Special Work Schedule Requirements:


Occasional need to work beyond regular work hours, holidays, or weekends as experiments demand.


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