The Institute for Systems Biology (ISB) seeks a highly motivated and talented Assistant, Associate, or Full Professor to join our faculty and lead transformative efforts in AI, machine learning, and computational biology to bridge the gap between basic science and next-generation medicine. The successful candidate will have a strong background in computational biology, statistics, machine learning/AI or a related field, and a passion for applying these techniques to address complex biological or medical problems.
Biomedical research pioneer Dr. Leroy Hood founded ISB in 2000 as the first-of-its-kind institute dedicated to systems biology. Unlike traditional academic departments, our faculty are cross-disciplinary, which enables us to take on big, complex problems. ISB is deeply committed to sharing our knowledge with society: we participate in the formation of companies, and strategically collaborate with healthcare systems and industry to improve human health and accelerate how science is conducted.
ISB’s computational capabilities are in biological modeling and simulation, machine learning, biostatistical methods, bioinformatics, medical informatics, applied to: genomics, phenomics and exposomics. ISB's technical capacities include genomics, transcriptomics, metagenomics, proteomics, metabolomics, imaging, and single-cell omics. Accordingly, ISB faculty develop novel measurement technologies, formal theories and computational tools to support all aspects of systems biology and systems medicine, and these unique resources are shared across the institute.
ISB’s affiliation with Providence, one of the largest not-for-profit health care systems in the United States, gives ISB access to unique resources including clinical trials, patient samples, 30 million electronic health records (EHRs), imaging, and the ability to translate discoveries into clinical applications that benefit patients.
Qualifications:
Candidates should have a Ph.D. or equivalent and have demonstrated the ability or potential to conduct independent, transformative research, and have a strong publication record to attract external research funding. The candidate should have a compelling research vision and a program that bridges computational innovation with translational applications, a plan for fundraising from federal (NIH, NSF, etc.) and other sources (philanthropy, foundations, etc.), and a mentoring plan for postdocs and students at all levels.
Responsibilities:
- Establish and maintain a research program in applied mathematics, statistics, computer science or data science to investigate fundamental biological processes and their relevance to human health.
- Pioneer innovative computational frameworks to integrate multimodal biological and clinical data, such as genomics, proteomics, phenomics, or specialized domains, such as deep immunophenotyping, imaging, health dynamics, and spatiotemporal omics data that can drive new scientific paradigms or personalized medicine with actionable insights for patients.
- Develop and apply innovative methods to integrate data-driven and knowledge-based approaches for discovery of mechanisms and clinical decision support.
- Collaborate with other researchers within the institute and external partners to translate computational discoveries into real-world applications in health care, from prevention to detection to treatment of diseases.
- Secure external funding to support research activities and expand the scope of the research program.
- Mentor graduate students, postdoctoral fellows, and undergraduate students.
- Contribute to the institute's research and educational mission.
Application Instructions:
Interested applicants should apply on ISB’s Careers page https://isbscience.org/careers/. Required materials include curriculum vitae, a 1-2 page cover letter, a 3-4 page research statement, a 1-page statement on mentoring philosophy, and a 1-page statement on contributions to/experience with diversity, equity, and inclusion. ISB is committed to creating a diverse environment and is proud to be an equal opportunity employer. Women and diverse candidates are strongly encouraged to apply and all qualified applicants will receive consideration for employment, without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, protected veteran or disabled status, or genetic information.
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