The Department of Biochemistry at Virginia Tech invites applications for an academic-year, tenure-track Assistant Professor in Computational and Systems Biochemistry. The successful candidate will establish an independent, internationally recognized, externally funded research program that advances fundamental understanding of biochemical systems. Research may develop novel computational methodologies or apply advanced computational tools to important biological questions, particularly in collaboration with experimental researchers. Areas of interest include bioinformatics, computational genomics, proteomics, metabolomics, systems biochemistry, multi-omics integration, and applications of artificial intelligence and machine learning to biochemical processes. Research integrating large-scale biological datasets with molecular mechanisms, metabolic pathways, regulatory networks, and biochemical function is particularly encouraged. The Department has collaborative strengths in infectious disease, microbial physiology and biochemistry, molecular genetics, computational modeling and simulation, and drug discovery. The position is within the College of Agriculture and Life Sciences at Virginia Tech, a land-grant institution with opportunities to connect computational and systems-level research to plant and animal health, agricultural biotechnology, microbial systems, food science, and environmental sustainability. Research infrastructure includes core facilities for mass spectrometry, short- and long-read sequencing, nuclear magnetic resonance spectroscopy, imaging and microscopy, and advanced research computing. The position is 70% research and 30% teaching. The faculty member is expected to develop a competitive externally funded research program, publish scholarly work, mentor undergraduate and graduate researchers, and contribute to undergraduate and graduate teaching in biochemistry and related computational disciplines. There may be opportunities to develop courses in the candidate’s area of expertise. The successful candidate will contribute to departmental service and support a welcoming and inclusive academic environment. Occasional travel to conferences is required.
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Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree