The lab of Chris Sander, in collaboration with Debora Marks, is hiring two postdocs to work on AI for cancer risk prediction, cell biology, and protein design. Join us to develop and apply machine learning and statistical physics methods for impactful research in human disease and synthetic biology.
We are in the department of systems biology and collaborate with research groups in the Boston area, including the Ludwig Center and the Broad Institute, and with researchers in the US, Canada, Denmark, Germany, China, and the UK.
Areas of focus:
- Cancer Risk Prediction: Use machine learning to identify patients at high risk for aggressive cancers so they can be enrolled in interception programs for prevention, early detection and early-stage treatment. On github: CancerRiskNet.
- Cell State Dynamics: Develop computational models from large-scale experiments to link novel perturbations with molecular and phenotypic changes, guiding therapeutic developments and cell biological experiments. On github: CellBox, scPerturb.
- Protein Function and Design: Predict protein function from sequences, design novel proteins for environmental or therapeutic purposes, and collaborate on engineering beneficial gene and protein modules. See: bit.ly/betalacdesign
PhD in biology, medicine, mathematics, computer science, physics, chemistry, or engineering.
Send CV, bibliography, statement of research interest (~1 page), and names of 3 references to sander.research #at& gmail &dot% com.