Assistant Professor of Biomedical Data Science
Work type: University Tenure Line
Location: Stanford University
Categories: School of Medicine
The Department of Biomedical Data Science (DBDS) at Stanford University seeks two faculty members to join the Department as Assistant Professors on the University Tenure Line. One of these faculty will be additionally jointly appointed as a Core Investigator at the Arc Institute. The successful candidates will be expected to contribute creatively and in depth to the analysis of biomedical data and their use to advance science and health. A PhD or equivalent degree in data science, biostatistics, statistics, biomedical informatics, clinical informatics, computer science, biomedical engineering or a related area is required.
The predominant criterion for appointment in the University Tenure Line is a major commitment to research and teaching. In line with the mission of the department, the research agenda of the faculty member should include the development and application of data analysis methods to address questions in biomedicine leveraging artificial intelligence (AI), machine learning, informatics, mathematical modeling, optimization and/or statistics. We anticipate that the successful candidate will devote 70–80% time to research and the remainder to teaching and other responsibilities.
For the joint position between DBDS and Arc, we are particularly interested in candidates with expertise on computational biology. The individual will hold a Stanford DBDS appointment with all rights and privileges afforded DBDS faculty. In addition, the Arc Core Investigator will have office and research space with the Arc Institute, and receive all rights and privileges afforded by the Arc Institute. For this joint appointment, DBDS and Arc are conducting independent search processes and candidates will be evaluated and selected by both committees. Two separate applications are required (see below).
For the position that will be housed entirely in DBDS, we welcome applications from the broad field of biomedical data science. We are especially interested in recruiting candidates with expertise in one or more of the following areas: large language models, generative AI, deep (reinforcement) learning, integration of -omics, imaging and EHR data, and/or statistical methods for complex data (e.g., high dimensional data and multi-level data).
Candidates need to indicate to which position they are interested in through the application process (interest in both positions is welcome, see instructions below).
Individuals appointed as Assistant Professors in the UTL will have completed one or two years of postdoctoral research experience. Their accomplishments during graduate and postgraduate training should already have stamped them as creative and promising investigators. If these individuals have not had formal teaching experience, they should have demonstrated during their postdoctoral training a commitment to develop the skills necessary for first-rate teaching. In short, the successful candidate must have demonstrated true distinction (or the promise of achieving true distinction) in research, and the capability of sustaining first-rate performance (or the promise of this) in teaching appropriate to the programmatic need upon which the appointment is based.
The initial term of appointments will be four years. (2.4.J. Specific/Supplementary Criteria for Assistant Professors—Stanford School of Medicine Handbook)
The expected base pay range for this position is: $175,000-$242,000. It does not include all components of the School of Medicine’s faculty compensation program or pay from participation in departmental incentive compensation programs. For more information about compensation and our wide-range of benefits, including housing assistance, please contact the hiring department.
Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years in rank, training, and field or discipline; internal equity; and external market pay for comparable jobs.
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford also welcomes applications from others who would bring additional dimensions to the University’s research, teaching and clinical missions.
Interested candidates should submit following materials via the portal https://facultypositions.stanford.edu/en-us/job/494643/assistant-professor-of-biomedical-data-science:
- Cover letter
- Curriculum Vitae
- Research statement (3-5 pages)
- Teaching statement (1-2 pages)
- Two representative publications
- Three letters of recommendation
The cover letter should indicate to which position the candidate intends to apply (joint with Arc or not) and candidates interested in both positions should submit two separate cover letters.
The Department of Biomedical Data Science, School of Medicine, and Stanford University value faculty who will help foster an inclusive academic environment for colleagues, students, and staff with a wide range of backgrounds, identities, and outlooks. Candidates may choose to include as part of their research and teaching statements a brief discussion about how their work and experience will further these ideals. Additional information about Stanford’s IDEAL initiative may be found here: https://ideal.stanford.edu/about-ideal/diversity-statement.
Candidates interested in the joint position with Arc are required to additionally apply through the Arc Institute here: https://arcinstitute.org/jobs/faculty-and–fellows, where more information on all aspects of the Core Investigator role, including salary ranges, is provided.
Applications will be reviewed starting November 3rd, 2023, until the position is filled.
For questions, please contact the Search Chair, Chiara Sabatti, at firstname.lastname@example.org.
Advertised: Pacific Daylight Time
Program Coordinator and Executive Associate
The Department of Biomedical Data Science (DBDS) in the Stanford University School of Medicine is a diverse, equitable, and inclusive group at the forefront of AI and precision health innovation. Our world-renowned faculty work on a variety of complex problems that create advancements in healthcare treatments and therapies. The DBDS administration is a team-first organization that is interdependent on its members to meet the demands of all faculty and students. We are seeking an excellent experienced administrator to fulfill the role of Program Coordinator and Executive Associate to our Department Chair. The incumbent will serve as a primary strategic partner to the Department Chair helping to plan and execute all programs and projects under her purview. To be successful, this position needs to be independent, strong, detail-oriented, personable, and able to cope with the demands of a very challenging and rewarding position.
Postdoctoral Fellowship in Population Outcomes Simulation Modeling at Stanford University
Postdoctoral Fellowship in Population Outcomes Simulation Modeling is available in Dr. Sylvia Plevritis’ Lab located in the James H. Clark Center at Stanford University. The fellowship will involve the development and application of computer simulation modeling to study the impact of alternative cancer screening and treatment strategies on cancer incidence and mortality rates in the US population and inform health policy. A major focus of the research will be focused on simulating the impact of breast and/or lung cancer screening guidelines and the impact of treatment on disease recurrence. The ideal candidate should have a Ph.D. in a field related to simulation modeling (i.e. operations research, applied mathematics) or a field that involves training in statistical analysis of clinical data (i.e. biostatistics, health-outcomes research, epidemiology). Experience in stochastic simulation modeling, Monte Carlo methods, parameter estimation, survival analysis and computer programming (R and Python) is critical. Knowledge of cancer epidemiology, cancer screening and treatment trials and analysis of cancer registry data is a bonus. Excellent verbal and written communication skills are necessary. Applicants should submit a cover letter, CV and 3 references to Sonoko Rooney, Executive Assistant to Dr. Plevritis, email: email@example.com with subject line “Population Outcomes Simulation Modeling.”
The expected base pay for this position is the Stanford University required minimum for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY24 minimum is $73,441.
This position is for two-years, full-time. The ideal candidate is expected to work on-site 5-days per week and attend weekly lab meetings.
Stanford University is an equal opportunity employer.
Two postdoctoral positions in microbial genomics and single cell genomics (Salzman Lab)
(Applications are ongoing as of 7/21/23)
We are recruiting two postdoctoral scholars to conduct research in:
- Microbial and host-microbial genomics: To study the mechanisms or RNA processing and those underlying microbial evolution and its relationship to host response in the context of disease.
- Single cell genomics: To study RNA splicing and noncoding RNA regulation in single cell genomic experiments using novel statistical and electrical engineering algorithmic design.
Candidates with the best fit will have a strong foundation in quantitative methods and will be familiar with or able to learn statistical genomic approaches taken in our lab as well as general statistical modeling. These projects will entail collaborative work or optional direct work on biochemical validation of computational predictions.
To apply, contact firstname.lastname@example.org.
Post-Doctoral Positions in Genetic Epidemiology and/or Statistical Genetics (Witte Lab)
(Applications are ongoing as of 7/21/23)
The Witte lab has openings for enthusiastic post-docs to work on the development of analytical methods and their application to cancer and other diseases / traits. We offer flexibility to pursue projects broadly related to the lab’s efforts in:
- Developing and applying novel approaches for the analysis of polygenic risk scores in diverse populations
- Evaluating pleiotropy and co-heritability of different phenotypes
- Incorporating genetic information to improve biomarker screening for disease (e.g., prostate specific antigen in cancer)
- Analyses of sequence data and rare variants