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  • Tenure-Track/Assistant Professor Faculty (PhD)…

    Johns Hopkins University (Baltimore, MD)



    Apply Now

    The candidate will join a transdisciplinary research environment, which encourages team science projects

     

    to rapidly advance new technologies and methodologies into clinical / translational studies. The Division

     

    of Quantitative Sciences offers unique opportunities for research and teaching opportunities in the rich

     

    computational biology community spanning many Institutes across Johns Hopkins University, including

    the Departments of Biomedical Engineering, Biostatistics, and Applied Mathematics and Statistics and

    the Convergence Institute and Bloomberg Kimmel Immunology for Cancer Immunotherapy. This

    collaborative, transdisciplinary research environment promoted in the Quantitative Sciences Division and

    the broader Johns Hopkins University fosters a diverse and inclusive community. Primary research focus

     

    should be dry lab cancer research leveraging computational biology, data science, and machine learning.

     

    We offer a competitive salary, benefits package, and start-up package.

    Duties and Responsibilities:

    ? Advance a research program in computational oncology, cancer systems biology, computational

     

    immunology, or genomics. Broadly, this will include development and applications of single-cell

     

    and imaging technologies, multi-omics analysis, mathematical modeling, and/or artificial

     

    intelligence and machine learning for cancer.

     

    ? Lead team science data science initiatives with cancer biologists, technology developers, and

     

    clinical investigators in Sidney Kimmel Comprehensive Cancer Center, Cancer Center Institutes,

     

    and broader Johns Hopkins University.

     

    ? Teaching computational oncology in research and didactic courses and mentoring teams of

     

    diverse trainees across the Johns Hopkins University.

     

    Tenure Track Faculty: Suitable candidates will hold a Ph.D. in computational biology, bioinformatics,

    biostatistics, computer science, physics, data science and machine learning, or similar field, with interest

    and experience in applications to cancer. The successful candidate will be primarily focused on

     

    computational research, and will have opportunities to develop a robust dry lab research program.

     

    The Johns Hopkins University is committed to active recruitment of a diverse faculty and student body.

     

    The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected

    veterans and individuals with disabilities, and encourages applications from these and other protected

    group members. Consistent with the University's goals of achieving excellence in all areas, we will assess

     

    the comprehensive qualifications of each applicant

     

    Salary: 125,000-137,600

     

    Applicants should send a letter of application, Curriculum Vitae (including

     

    personal website URL if available), a research statement and at least three letters of reference directly

    Job Type: Full Time

    The listed salary range represents the minimum and maximum Johns Hopkins University offers for this position, based on a good faith estimate at the time of posting. Actual compensation will vary depending on factors such as location, skills, experience, market conditions, education, and internal equity. Not all candidates will qualify for the highest salary in the range.

     

    Johns Hopkins provides a comprehensive benefits package supporting health, career, and retirement. Learn more: https://hr.jhu.edu/benefits-worklife/.

     

    Equal Opportunity Employer

     

    All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

    EEO is the Law

    https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf

     


    Apply Now



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