Develop new methods and frameworks for uncertainty quantification, statistical inference, and experimental design to guide decision-making across the drug‑discovery pipeline.
Locations (3)
South San Francisco, California, United States
New York, United States
Basel, Basel-City, Switzerland
Compensation
The expected salary range for this position, based on the primary location of California, is $147,600 - 274,000. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance.
Responsibilities
Develop new methods and frameworks for uncertainty quantification, statistical inference, and experimental design
Contribute to and drive research projects that result in conference and/or journal publications and open‑source code
Foster cross‑organizational collaborations and applications
Engage actively in knowledge dissemination, presenting work at internal and external scientific conferences
Collaborate closely with teams in South San Francisco, New York, and Basel
Requirements
Ph.D. in Computer Science, Statistics, Applied Mathematics, Physics, Computational Biology, or related technical field
Nice to have: Experience with developing machine learning and/or statistical methods for biological/clinical data
Nice to have: Experience developing open-source packages
Develop new methods and frameworks for uncertainty quantification, statistical inference, and experimental design in drug discovery.
Locations (3)
South San Francisco, California, United States
New York, New York, United States
Basel, Basel-City, Switzerland
Compensation
The expected salary range for this position, based on the primary location of California, is $147,600 - 274,000. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance.
Responsibilities
Develop new methods and frameworks for uncertainty quantification, statistical inference, and experimental design
Contribute to and drive research projects resulting in conference and/or journal publications and open-source code
Foster cross-organizational collaborations and applications
Engage actively in knowledge dissemination, presenting work at internal and external scientific conferences
Collaborate closely with team in South San Francisco, New York, and Basel, Switzerland
Requirements
Ph.D. in Computer Science, Statistics, Applied Mathematics, Physics, Computational Biology, or related technical field
Nice to have: developing machine learning and/or statistical methods for biological/clinical data
