Faculty
Open Line, Open Rank, Artificial Intelligence Faculty Cluster Hire Search
Work type: Non-Tenure Line (Research), University Medical Line, University Tenure Line
Location: Stanford University
Categories: School of Medicine
Open Line, Open Rank, Faculty Cluster Hire Search
Stanford University School of Medicine
The Stanford University School of Medicine (SoM) is recruiting multiple faculty at the Assistant, Associate, or Full Professor in the University Tenure Line (UTL), University Medical Line (UML), or Non-Tenure Line-Research (NTL-R) through this AI (Artificial Intelligence) Faculty Cluster Hire Search. We are specifically interested in candidates who have experience developing and applying novel biomedical AI and data science methods that incorporate biomedical domain expertise to ensure relevance and impact to health and medicine. Candidates will be hired into one or more SoM department(s) and contribute to the research, educational, and if relevant, clinical activities.
This AI Faculty Cluster Hire Search aims to recruit a diverse group of experts dedicated to fostering growth of biomedical AI and data science both within our organization and beyond. These distinguished individuals will become integral members of a dynamic community, collaborating not only within their respective departments or institutes but also across the SoM and our university at large.
- The predominant criterion for appointment in the University Tenure Line is a major commitment to research and teaching.
- The major criteria for appointment for faculty in the University Medical Line shall be excellence in the overall mix of clinical care, clinical teaching, scholarly activity that advances clinical medicine, and institutional service appropriate to the programmatic need the individual is expected to fulfill.
- The major criterion for appointment for faculty in the Non-tenure Line (Research) is evidence of high-level performance as a researcher for whose special knowledge a programmatic need exists.
Faculty line and rank will be determined by qualifications and experience. The successful candidate must have an MD, MD/PhD, or PhD with substantial expertise in one or more aspects of biomedical data science enabled or enhanced by AI. The successful candidate will be expected to develop an independent research program that advances AI approaches to biomedical data science, with a focus on their use in basic, translational, clinical, and/or population sciences.
Examples of focus areas in basic science research include development of methods to determine molecular structures, accelerate development of novel therapeutics, elucidate stem cell biology, or enable regenerative medicine. Examples of focus areas in clinical research include the development of AI methods for integration and analysis of multimodal patient data, including laboratory tests, clinical notes, images and video across multiple scales, speech to text, physiologic assays, and functional evaluations. Clinical AI research domains span across medical specialties, including but not limited to cancer, neurology, neuroscience, cardiovascular disease, intensive care, mental health, peri-operative care, pain management, ophthalmology, pediatrics, radiology, pathology, and surgery. Examples of focus areas in population health research include pharmacoepidemiology, genetic epidemiology, environmental epidemiology, AI health policy, fairness, and the legal, regulatory, ethical, and economic considerations that underlie the responsible implementation of clinical decision support tools. Research in all of these areas will benefit from broad interactions and collaborations throughout the SoM, across Stanford University, and within the large and growing health systems of Stanford Medicine.
The successful candidate will be expected to teach students, residents, postdoctoral fellows and clinical fellows, and participate in relevant clinical and basic science conferences. They will have demonstrated the potential to achieve, or have a demonstrated record of achievement in relevant rigorous research. The Departments, 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.
Review of complete applications will begin on September 23, 2024, and will continue until the positions are filled.
Interested candidates should submit the following to apply:
- A detailed letter of research and teaching interest and if relevant, clinical specialty,
- A curriculum vitae,
- Three names of referees for letters of recommendation.
This role is open to candidates from multiple disciplines/specialties. The pay offered to the selected candidate will be based on their field or discipline. The expected base pay range for likely disciplines are listed below. Interested candidates whose discipline is not listed below may contact the hiring department for the salary range specific to their discipline/specialty.
Post-doctoral
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 julia.salzman@stanford.edu.
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
Research Assistant
Graduate Student RA-ship in Single Cell Analysis
Posted 2/8/24
A graduate student RAship in single cell analysis is available in Professor Sylvia Plevritis’ Laboratory located in the James H. Clark Center. The RA will contribute to development and application of computational tools for analyzing single-cell proteomic cancer datasets. The specific project will focus on methods to analyze the effectiveness of drug combinations using single cell proteomics data, generated using CYTOF, from primary cancer biospecimens. The RA will work closely with computational scientists and experimental molecular biologists to translate computationally-derived results into clinically relevant insights. Candidates must have a strong quantitative background, with graduate studies in computational biology, bioinformatics or related field including engineering, computer science, statistics, or mathematics. Strong knowledge in machine learning and programming (R, Python) are required. Experience with single call analytics and/or multivariate survival analysis is desirable. Excellent verbal and written communication skills are essential.
Applicants should e-mail a cover letter describing research experience, accomplishments and research interests and resume, under the following subject line: “RAship in Single Cell Analysis” to Corinne Beck (corinnebeck@stanford.edu).