Postdoctoral Fellow - Computational Biology & Medicine - Jhunjhunwala Lab

The Position

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Genentech.

Are you a highly passionate computational biologist looking to make a significant impact in cancer immunology? Join Genentech's Computational Sciences Center of Excellence as a Postdoctoral Fellow, where you'll conduct cutting‑edge research at the intersection of computational biology and oncology. This position offers a unique opportunity to be jointly mentored by experts in our Computational Biology and Medicine department and our Oncology Research organization.

The primary area of work is to study the T cell receptor (TCR) repertoires, their antigens, and their relevance to cancer and autoimmune disease. The successful candidate has a strong background in computational biology and machine learning. Research responsibilities will include (but not limited to) multi‑omics analysis of bulk and single‑cell sequencing data, developing deep learning models, and experimental design to test and validate hypotheses.

This is a fantastic opportunity to contribute to world‑class science in a leading biotechnology company.

• Candidates must have a PhD in Computational Biology or Computational Science. Alternatively, a PhD in Molecular Biology or Immunology with computational biology as the primary focus.
• Impactful researcher with one or more first‑author publications in high quality journals.
• Strong experience in application‑based computational biology, including single‑cell sequencing techniques.
• Strong experience in deep learning and AI.
• Pragmatic and focused researcher, driven to solve complex scientific problems independently and in a collaborative environment.
• Efficient oral and written communication skills are required.

Thrift, W. J. et al. Graph‑pMHC: graph neural network approach to MHC class II peptide presentation and antibody immunogenicity. Briefings in Bioinformatics 25 (2024).

Thrift, W. J. et al. HLApollo: A superior transformer model for pan‑allelic peptide‑MHC‑I presentation prediction, with diverse negative coverage, deconvolution and protein language features. bioRxiv (2022) doi:
10.1101/.519673.

Jhunjhunwala, S., Hammer,

C. & Delamarre, L. Antigen presentation in cancer: insights into tumour immunogenicity and immune evasion. Nat Rev Cancer 1–15 (2021) doi:
10.1038/s‑z.

Chen, J. et al. In silico tools for accurate HLA and KIR inference from clinical sequencing data empower immunogenetics on individual‑patient and population scales. Brief Bioinform bbaa
223‑ (2020) doi:
10.1093/bib/bbaa
223.

Capietto,

A.‑H. et al. Mutation position is an important determinant for predicting cancer neoantigens. J Exp Medicine 217, (2020).

Kong, Y. et al. Transposable element expression in tumors is associated with immune infiltration and increased antigenicity. Nat Commun 10, 5228 (2019).

Yadav, M. et al. Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing. Nature 515, 572–576 (2014).

The Genentech Postdoc Program provides access to world‑class seminars, professional development workshops, and networking opportunities.

The expected salary range for this position based on the primary location of California is $110,000 to $120,000. Actual pay will be determined based on experience, qualifications, geographic location, and other job‑related factors permitted by law. This position also qualifies for the benefits detailed below.

Relocation benefits are available for this job posting.

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.