The Chan Zuckerberg Biohub New York is seeking to investigate the fundamental mechanisms underlying disease and develop new technologies that will lead to actionable diagnostics and effective therapies by hiring a Computational Biologist.
Requirements
- PhD in Computational Biology, AI / Machine learning, Applied Statistics or a MS plus relevant job experience
- Background in relevant areas of biomedical science, demonstrating a deep understanding of cellular biology, transcription and protein signal transduction
- 2-4 years of post-doctoral and/or industry experience demonstrating the ability to implement, evaluate, and create new computational methodologies that leverage machine learning, statistics, and AI for biological research and discovery
- Experience in building and evaluating machine learning and/or neural network models on biological data, with a deep understanding of feature selection, regularization, model introspection, and interpretability
- Proficiency in using and modifying probabilistic learning or deep learning models such as RNNs, GNNs, protein sequence models, or natural language processing models
Responsibilities
- Contribute to a dynamic, innovative, and collaborative program that aligns with the mission of CZ Biohub NY
- Develop and evaluate cutting-edge computational methodologies using data generated from across all research groups and incorporating relevant available datasets to develop predictive models
- Collaborate within an interdisciplinary research environment to develop, test, and validate models
- Communicate progress and results with colleagues inside and outside of your team
- Publish and disseminate impactful findings through preprints (medRxiv, bioRxiv) and/or software repositories (e.g., GitHub)
- Work with the CZ Biohub team to patent and license technologies resulting from your research
Other
- Outstanding interpersonal and communication skills
- Demonstrated commitment to open science and alignment with the mission and values of CZ Biohub
- Ability to work collaboratively in a highly interdisciplinary environment
- PhD or MS degree in a relevant field
- 2-4 years of post-doctoral and/or industry experience
