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Postdoctoral Researcher in Computational Genomics and Cancer Data Science
2 months ago
We are seeking a highly motivated Postdoctoral Fellow to join our team in Computational Genomics and Cancer Data Science at Memorial Sloan Kettering Cancer Center. The successful candidate will have a strong background in machine learning and a passion for developing and applying quantitative methods to problems in translational cancer biology and cancer data science.
Key Responsibilities- Develop and apply deep learning and artificial intelligence methods to analyze large-scale datasets
- Work with clinical and biological scientists to advance and execute hypothesis-driven research
- Prepare and contribute to scientific manuscripts for publication in journals and conferences
- Collaborate with academic partners at other institutions and industry partners in biotech, health data, and big tech
- Engage with a vibrant community of researchers by presenting at internal work-in-progress meetings and external scientific conferences
- Ph.D. in Applied Mathematics, Machine Learning, Computational Biology, or Computer Science with emphasis on applications in molecular biology and/or computational pathology
- Strong programming skills (Python and/or R) and experience developing and training state-of-the-art computer vision models, such as vision transformers, using PyTorch for whole-slide image analysis
- Research experience in statistics and computational genomics, and familiarity with next-generation sequencing data and analysis tools
- Excellent oral and written English communication skills; experience in delivering oral scientific presentations and writing scientific articles
Competitive salary range: $55,439 – 100,940
Subsidized housing close to the MSK campus is available
Opportunity to work with a talented team of researchers and clinicians
Access to state-of-the-art computational infrastructure and unrivaled data resources
How to ApplyIf you have any questions about this opportunity, please contact Dr. Francisco Sanchez-Vega at [insert email address].
