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Bioinformatician
Postgraduate Position in Computational Biology – Yale School of Medicine Full-time NEW
Postgraduate position in Computational biology / Bioinformatics
Yale School of Medicine / Yale Cancer Center
Dr. Muneeb Alam and The Braun Lab (Yale Center of Molecular and Cellular Oncology / Yale Cancer Center / Yale School of Medicine) are seeking a highly motivated, computationally focused postgraduate with an interest in cancer immunotherapy and immunogenomics to join our translational research team. The anticipated start for this position will be in Spring/Summer 2026.
Dr. Alam is a surgeon-scientist and embedded investigator in The Braun Lab with an active research interest in surgical outcomes and response to immune-based therapies in patients with kidney cancer. His research employs multi-modal next generation sequencing strategies and patient-derived models to study the biology of kidney cancer. Dr. David Braun is an internationally recognized physician-scientist whose research has helped to elucidate genetic and immunologic features that impact response to immune checkpoint inhibitors (Braun, Nature Medicine, 2020) and to define the immunologic changes that occur with progression to advanced disease (Braun, Cancer Cell, 2021) in kidney cancer.
The ideal candidate will have a strong background in computer/data science (including statistics), knowledge of R and python, and experience with high performance computing clusters. They are expected to be collaborative in nature, an independent learner, be able to problem solve, and have outstanding oral and written communication skills.
Education: The postgraduate associate will have an education plan in line with the individual’s goal of pursuing professional school (medical and/or graduate school). This includes education regarding patient-oriented research, translational research, cancer biology and immunology, and scientific communication. The successful applicant will have opportunities to present at lab and departmental meetings and to submit abstracts for presentation at regional/national conferences with the goal of manuscript publication.
Training: Postgraduates will develop skillsets in bulk and single-cell genomic analysis and the creation/maintenance of computational pipelines for immunogenomic analysis (including T cell receptor sequencing analysis and prediction of tumor antigens). They will also gain familiarity with spatial sequencing technologies such as Visium and Xenium.
Mentoring: The Braun Lab is committed to mentoring postgraduates with a strong track record of postgraduate mentees ultimately going to medical school or other professional schools. The postgraduate will meet at least weekly with Dr. Alam with additional dedicated meetings for mentoring and career development. The successful applicant will participate in weekly lab meetings, attend weekly single-cell analysis meetings, and have access to regular seminars and lectures across Yale School of Medicine.
Qualifications: Applicants should be highly motivated, able to work well in a multidisciplinary team, and have strong quantitative skills. A Bachelor’s degree is required at the time of starting the position, preferably in computer science, data scientist, computational biology, biostatistics, or the biological sciences (with quantitative experience).
Process to apply: Interested applicants should send a CV and contact information for 3 references to listed email. Applications will be assessed on a rolling basis.
Yale’s Equal Employment Opportunity Statement:
The University is committed to basing judgments concerning the admission, education, and employment of individuals upon their qualifications and abilities and seeks to attract its faculty, staff, and student body qualified persons from a broad range of backgrounds and perspectives.
Additionally, in accordance with this Policy and as delineated by federal and Connecticut law, Yale does not discriminate in admissions, educational programs, or employment against any individual on account of that individual’s sex; sexual orientation; gender identity or expression; pregnancy, childbirth or related conditions; race; color; national or ethnic origin; religion; age; disability; protected veteran status, or other protected classes as set forth in federal and Connecticut law.