Postdoctoral fellow in the experimental and/or computational study of alternative mRNA splicing

Associate Professor Justin B. Kinney seeks a postdoctoral fellow to carry out experimental and/or computational work aimed at understanding how genomic sequence quantitatively controls alternative mRNA splicing in humans. Research pursued by the postdoctoral fellow will likely involve the use of massively parallel reporter assays (MPRAs) and/or the development of deep neural network models.
 
 The Kinney Lab develops experimental, computational, and mathematical approaches for deciphering the quantitative molecular mechanisms of gene regulation. Their experimental work centers on the use of MPRAs, a technology that Dr. Kinney and his lab have pioneered and continue to advance. They also develop machine learning approaches, including deep learning strategies, for extracting quantitative models of sequence-function relationships from MPRA datasets and for interpreting these models in terms of underlying biophysical mechanisms. Please visit http://kinneylab.cshl.edu/ for more information.
 

Candidates must have (or soon receive) a PhD in Biology, Biochemistry, Computational Biology, Biophysics, Bioengineering, or related discipline. Candidates must also have one or more first-author research publications and/or pre-prints in the field of quantitative biology, broadly defined. Candidates should have strong written and oral communication skills and the ability to navigate and synthesize relevant research literature. Additional useful skills include a working knowledge of Python, experience with the computational analysis of biological sequence data, experience with public genomic databases, experience with deep learning frameworks (e.g., TensorFlow, PyTorch, or JAX), and an understanding of statistical mechanics at the undergraduate level.
How to Apply:
For immediate consideration, please complete the online application found here: https://www.schooljobs.com/careers/cshl/jobs/4147850/postdoctoral-fellow-in-the-experimental-and-or-computational-study-of-alternative?keywords=kinney&pagetype=jobOpportunitiesJobs   Position ID 00583

Environment
The Kinney Lab is situated in the Simons Center for Quantitative Biology at Cold Spring Harbor Laboratory (CSHL). The Simons Center is a closely knit community of researchers that use machine learning and other quantitative approaches to study diverse topics in genomics, evolution, biophysics, immunology, and neuroscience. CSHL is a world-renowned non-profit research institution that is home to eight Nobel Prize winners and consistently ranks among the world’s top institutions in research impact per scientist. Members of the CSHL community benefit from the vibrant Meetings and Courses Program, which hosts leading conferences in many biological disciplines. The Simons Center sits on CSHL’s beautiful main campus, which is located on the north shore of Long Island and is readily accessible from New York City via the Long Island Rail Road. We have had researchers with a variety of backgrounds and believe in the importance of diversity, equity, and inclusion. Please visit https://www.cshl.edu/ for more information.
Compensation & Benefits
Our employees are compensated in many ways for their contributions to our mission, including competitive pay, exceptional health benefits, retirement plans, paid time off, and a range of recognition and wellness programs. Visit our CSHL Benefits , Postdoctoral Landing  sites to learn more. The salary for this role is $73,500 per annum. The salary range or hourly rate listed is a good faith determination of potential base compensation that may be offered to a successful applicant for this position at the time of this job advertisement and may be modified in the future. When determining a base salary and/or rate, several factors may be considered as applicable (e.g., years of relevant experience, education, credentials, and internal equity).
We strongly recommend to be fully vaccinated for COVID-19 however; it is not a requirement for employment.
CSHL is an EO/AA Employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status. VEVRAA Federal Contractor