Openings in DBDS

Faculty

Assistant Professor of Biomedical Data Science 

Work type: University Tenure Line
Location: Stanford University
Categories: School of Medicine

Currently in interviewing process. 

 

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.

Information about the Department of Biomedical Data Science is available at https://dbds.stanford.edu. Information about the Arc Institute is available at https://arcinstitute.org.

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:

  1. Cover letter
  2. Curriculum Vitae
  3. Research statement (3-5 pages)
  4. Teaching statement (1-2 pages)
  5. Two representative publications
  6. 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-andfellows, 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 sabatti@stanford.edu.

Advertised: Pacific Daylight Time
Applications close:

 

Post-doctoral

Warren Alpert Computational Biology & AI Scholars Postdoctoral Program
April 2nd, 2024

The Warren Alpert Computational Biology & AI Scholars program (WA CBAI) provides support for one Postdoctoral Fellow in the Department of Biomedical Data Science (DBDS) per year who is conducting research focused on AI and the underlying science in developing therapeutics and treatment modalities. The research should be related to:

  • Multimodal data integration of data assets generated across the biomedical spectrum, such as molecular, tissue, anatomical, patient, biosensory and/or population level data.
  • Development of novel AI/ML methods to analyze this rich data for new insights into addressing diseases at all stages.
  • Human-centered research linked to patient phenotypes and connected to preclinical and experimental platforms with collaborations in basic sciences for functional validation and therapeutic development.
  • Research at the intersection of computational biology and AI in biomedicine.This is a new Scholars program to be launched in September 2024. During the 1-year Postdoc Scholarship, the Postdoc Fellow will receive full-time salary along with a range of health and other benefits that Stanford provides for postdoctoral scholars. There will also be opportunities to connect with a growing community of faculty, graduate students and other Postdocs involved in Computational Biology & AI.Eligibility:The program is designed for Postdoctoral Fellows at Stanford currently who wish to extend for 1 year, or new Postdoctoral Fellows who are available to start a 1-year position in September 2024. This program is for US citizens and permanent residents only. Candidates must have completed a PhD degree within 3 years or an MD degree within 6 years of application. Candidates must have at least 51 months of research experience. Candidates can not have an appointment with another institution or be employed elsewhere concurrently with this postdoctoral position.Application Process:Interested candidates who meet the eligibility criteria should submit their resume or CV, short research proposal (2 pages max not including references and figures; 12 point font, and 1 inch margins on left/right, and top/bottom), and faculty letter of support acknowledging that they have read the candidate’s proposal for this Scholarship, and complete the online registration form by May 31st. See below timeline for details.

Applications will be reviewed by a selection committee composed of DBDS faculty and staff.

Selection Criteria:

Applicants will need to include a short research proposal (2 pages max, not including references and figures), and answer a few questions about why they are interested in the WA CBAI Scholars program. Applicants will also need to include their resume or CV, and a faculty letter of support for the proposed project.

Selection will be based on:
(1) Topic of the research, and relevance to computational biology and AI
(2) Potential impact and innovation of the research
(3) Relevant prior experience, and how this research is different from PhD experience
(4) Faculty advisor letter of support
(5) Contributions to Community: experience with mentoring students, collaboration within a department, etc.

2024 Timeline:

April 2nd: May 31st: June 30th: Sept 1st:

Application opens
Application closes
First WA CBAI Postdoc Scholar selected and everyone notified Start date with funding for 12 months

Program for Selected Scholars:

The WA CBAI Postdoc Scholar will be supervised by their PI in the Department of Biomedical Data Science. The Postdoc Scholar will join a new CBAI community which will include WA CBAI PhD and MS Scholars selected as well to begin in fall 2024.

The WA CBAI Postdoc Scholar will be expected to participate in the following programs:

●  Quarterly gathering with all Warren Alpert CBAI Scholars and faculty involved in the
program. There may be guest speakers, mentoring opportunities, and time to share updates
with other scholars.

●  Poster presentation at annual symposium on Computational Biology and AI (starting in
2026)

●  Poster presentation at Department of Biomedical Data Science annual DBDSFest in spring
quarter.

●  Attendance and poster presentation at the annual DBDS retreat in September with all the
students, faculty, and staff in the department. The department will cover lodging and food
expenses at the retreat.

●  The Postdoc Scholar will also have funding to attend one conference per year related to
Computational Biology and AI.

●  The Postdoc Scholar will be expected to briefly share their research at the annual CBAI
Scientific Advisory Board meeting.

● The Postdoc Scholar will help mentor the PhD and MS Warren Alpert Scholars, and is expected to contribute to the development & outreach of the WA Center of Excellence

Notification:

Selected scholars will be notified by June 30th, 2024. We will plan a kick-off meeting with the PhD and MS Scholars, and the faculty involved in this new initiative in October 2024. Scholars will also be announced on the DBDS home page, DBDS weekly digest and on DBDS social media.

Postdoctoral Fellowship – Cancer Biologist on Tumor Spatial Biology (Plevritis Lab)

Posted 12/11/23

Description:

A cancer molecular biologist at the level of Postdoctoral Fellow is sought to work in a hybrid (wet/dry) systems biology laboratory of Professor Sylvia Plevritis at Stanford University to study tumor spatial biology via single cell spatial analysis of the tumor microenvironment. Projects aim to reveal molecular mechanisms of drug resistance based on intercellular and intracellular regulation, with a focus on combination therapies that account for cell-cell interactions. Experimental model systems will include cancer cell lines, organoid models, and human tumors and may involve mouse models. Projects will primarily rely on drug screening, manipulation of gene expression in cell culture, patient-derived models and possibly in-vivo assays (xenograft, orthotopic, and transgenic models).

Required Qualifications:

  • Experience with mammalian cell culture models, fluorescence microscopy and
    use of lentiviral delivery systems or CRISPR-Cas9 gene editing is required.
  • Interests in learning new technologies is mandatory. Basic R programming skills
    or the interest in learning programming is highly desirable.
  • Experience with flow cytometry, genomics, spatial -omics and/or mass cytometry analysis is desirable.
  • A successful candidate will interact closely with computational biologists and be
    responsible for designing and executing experiments that will, in part, validate
    computationally-derived regulatory interactions of the tumor microenvironment.
  • The ideal candidate should have a PhD in the field of molecular and cellular
    cancer biology, relevant publications, and high fluency in English.

Required Application Materials:

  • Cover letter describing relevant research experiences, accomplishments, interests, and goals
  • Curriculum vitae
  • Name and contact information of three references

How to Apply:

Please complete a questionnaire and upload your documents here. Applications will be accepted until the position is filled.

Questions should be directed to Corinne Beck at corinnebeck@stanford.edu

Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.

 

Postdoctoral Fellowship in Computational Spatial Biology (Plevritis Lab)

Posted 12/11/23

Description:

We are seeking a postdoctoral fellow in computational spatial biology to work in the laboratory of Professor Sylvia Plevritis in the Department of Biomedical Data Science at Stanford University. This research opportunity will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and multiplexed immunofluorescence in-situ images, in the study of immune-stromal-cancer interactions in metastatic progression. The scholar will aim to understand mechanisms through which the tumor microenvironment impacts tumor invasion and metastatic progression, using high-throughput data derived from cellular subpopulations within tumors. The individual will work closely with experimental biologists to translate computationally-derived results into experimentally testable hypotheses and analyze the resulting data from the experiments.

Required Qualifications:

  • Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including bioengineering, computer science, statistics, or mathematics.
  • Strong knowledge in bioinformatics, machine learning, statistics and programming skills (R, Python, or MATLAB) are required.
  • The ideal candidate should demonstrate a record of publications in the area.
  • Knowledge in one or more of the following areas is desirable: single-cell profiling technologies, spatial omics data, immunology and cancer systems biology.
  • Excellent verbal and written communication skills are essential.

Required Application Materials:

  •  Cover letter describing relevant research experiences, accomplishments, interests, and goals
  • Curriculum vitae
  • Name and contact information of three references
  • How to Apply: Please complete a questionnaire and upload your documents here. Applications will be accepted until the position is filled.Questions should be directed to Corinne Beck at corinnebeck@stanford.edu. Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.

Postdoctoral Fellowship in Population Outcomes Simulation Modeling at Stanford University

Posted 7/21/23

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 contact information of 3 references to Corinne Beck, Plevritis Lab Program Manager, at corinnebeck@stanford.edu 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 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).