Postdoctoral Fellow - Scientific Machine Learning in Clinical Drug Development, Lemaire Lab
We have an opening for a postdoctoral fellow or artificial intelligence (AI) residency in the Modeling & Simulation group within the Clinical Pharmacology department at Genentech. We are looking for a talented and innovative individual wishing to apply their expertise to solve concrete problems in clinical drug development. The project is to tackle the difficult problem of identifying combination therapies that will provide durable benefit to a large number of cancer patients. The idea is to combine an existing mechanistic model of the biology with a deep-learning framework that will be mutually beneficial to one another, allowing to assess and identify novel groundbreaking anti-cancer treatment combinations. During this residency, you will interact and learn from some of the most talented scientists in their field of Clinical Pharmacology, Clinical Development, Biomarker Development, Biological Research, as well as with AI and modeling scientists. This research is expected to lead to influential publications in top-tier journals. It is a challenging role, but it is offering tremendous prospects for learning, development and impact. This position is for 2 to 4 years and is opened internationally.
In addition to building a mechanistically-driven deep learning framework for the comprehensive assessment of anti-cancer combinations, the candidate will be responsible for compiling and processing all data necessary for the project, set up the computational framework required for the project, work closely with other modeling and AI scientists and benefit from each other expertise, learn the biology and the clinical aspects of anti-cancer treatments as needed and collaborate with non-modeling scientists from other departments.
Other responsibilities include:
- Present results in non-technical terms at cross-functional teams, department meeting, and/or review committees.
- Summarize results in posters for presentation in internal or external conferences.
- Write manuscripts summarizing the accomplished work.
- Adapt and thrive in an interactive, team-oriented culture.
Requirements:
- Ph.D. in physics, applied mathematics, statistics, computer or computational sciences, or in an engineering field such as biomedical informatics, or a related discipline
- Experience with developing deep-learning systems is required.
- Experience or knowledge with neural network-based ODE systems, such as neural-ODE or Universal Differential Equations is preferred.
- Experience with statistical modeling and machine learning analysis is required.
- Experience with ODE-based, stochastic, or agent-based systems modeling would be considered a plus (especially of biological systems).
- Proficiency in scientific computing programming using Matlab, Mathematica, Julia, R or Python is required. Experience with Matlab would be considered a plus.
- Strong communication and interpersonal skills, enthusiasm to contribute in a multidisciplinary environment, driven by challenges, scientific curiosity.
- Publication record of substantial/influential work is expected.
- Creative, resourceful, and eager to learn and discover are other qualities we are looking for.
Relocation benefits are available for this job posting.
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