Postdoctoral Associate - Immunology
- University of Pittsburgh
- Location: Pittsburgh, PA
- Job Number: 7112365 (Ref #: pt10069)
- Posting Date: Oct 1, 2022
- Application Deadline: Open Until Filled
Both projects provide ample opportunities both for very creative method development, and for applications of these techniques to questions of very high relevance to human health and disease. Further, through the IGVF consortium, the postdoctoral researcher will have exposure to and opportunities to collaborate with leaders in genomics at 24 other centers (including at MGH/Harvard, Stanford, Duke UW, UCLA, UCSD) across North America. Our research program is highly interdisciplinary, and we provide a training environment tailored to individual mentees, based on their background and interests. Trainees will be provided several career development opportunities including support for conference travel as well as mentorship and guidance to apply for funding/career development awards. Visa sponsorship, if applicable, is available. Salary will be commensurate with experience.
Qualifications or Expectations:
- Candidates must have a PhD in a quantitative discipline. Possible disciplines include, but are not limited to, computational biology, bioinformatics, systems biology/systems immunology, bioengineering/biomedical engineering, genomics, computer science and statistics.
- Candidates with training in immunology would be preferred, but this is not essential to apply to this position.
- The ideal candidate will have training in machine learning (especially deep learning), and requisite programming skills.
- Trainees will be provided several career development opportunities including support for conference travel as well as mentorship and guidance to apply for funding/career development awards.
- Visa sponsorship, if applicable, is available. Salary will be commensurate with experience.
Duties or Responsibilities:
- 1. The first direction funded by NIAID DP2 (PI: Jishnu Das) focuses on the use of a novel 3D protein network approach to uncover immunomodulatory molecular phenotypes in HIV and influenza. There are several sub-projects that involve the use of creative feature-based ML as well as deep learning approaches to construct 3D networks as well as infer immunomodulatory molecular phenotypes. A DP2 grant is given to innovative high-reward research (https://grants.nih.gov/grants/guide/pa-files/par-20-259.html) and this provides a very exciting opportunity for the postdoc to work on transformative ideas at the interface of systems biology and infectious disease.
- 2. The second direction is funded by a NHGRI U01, a large collaborative center-grant multi-PI grant (PIs: Jishnu Das, Harinder Singh and Nidhi Sahni). Through this grant, we are one of the centers in NHGRI’s latest IGVF consortium, a massive effort spanning 25 centers across North America to characterize the impact of genomic variation on function (https://www.genome.gov/Funded-Programs-Projects/Impact-of-Genomic-Variation-on-Function-Consortium). Here, sub-projects will focus on the use of ML/deep learning techniques to assemble a dynamic gene regulatory network in primary human B cells and quantify the impact of autoimmune-disease associated GWAS variants on these networks.
For more info about this position, visit:https://www.jishnulab.org/