CZ Biohub Chicago is seeking to advance biological research and discovery through innovative computational methodologies that leverage machine learning, statistics, and AI.
Requirements
- Working knowledge in building and evaluating machine learning and/or neural network models on biological data
- Proficiency in using and modifying probabilistic learning or deep learning models such as Transformers, GNNs, protein sequence models, or natural language processing models
- Working knowledge working with large-scale compute/cluster infrastructure
- Strong background in statistics, statistical learning, computational biology or mathematics
- Experience with DNA and protein foundation models
- Experience with single cell multiomics, including scRNA-seq, scATAC-seq and and CITE-seq
- Background in data curation and management for large-scale genomic datasets
Responsibilities
- Develop and evaluate cutting-edge computational and AI/ML methodologies
- Collaborate within an interdisciplinary research environment
- Publish and disseminate impactful findings through preprints and/or software repositories
- Work with the CZ Biohub team to patent and license technologies resulting from research
- Communicate progress and results with colleagues inside and outside of the team
- Contribute to a dynamic, innovative, and collaborative program that aligns with the mission of CZ Biohub Chicago
- Engage with colleagues throughout the Biohub to uphold values of scholarly excellence, innovation, open communication, hands-on hacking, and partnership
Other
- PhD in Computational Biology, AI / Machine learning, Applied Statistics, or relevant field
- 1-2 years of post-doctoral and/or industry experience
- Outstanding interpersonal and communication skills
- Proven track record of innovation, and ability to work collaboratively
- Diversity of thought, ideas, and perspectives
- Commitment to cultivating an inclusive organization
