DURATION: 12 MONTHS

Description

• We are looking for talented Machine Learning Engineers to join Prescient Design, a division devoted to developing structural and machine learning based methods for molecular design within Genentech’s Research and Early Development (gRED) organization.
• The successful candidate will manage projects deploying new techniques for machine learning based molecular optimization for the analysis and design of small and large molecule drugs within target-driven design campaigns.
• Special focus will be given to engineering pipelines for probabilistic molecular property prediction and Bayesian acquisition for active learning based drug discovery.
• Additional activities may extend to include engineering pipelines for molecular generative modeling.

QUALIFICATIONS:

• PhD degree in a quantitative field (?e.g.?, Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics), or MS degree and 3+ years of industry experience.
• Demonstrated experience with machine learning libraries in production-ready workflows (e.g., PyTorch + Lightning + Weights and Biases)
• Record of achievement, including at least one high-impact first author publication or equivalent.
• Excellent written, visual, and oral communication and collaboration skills.

ADDITIONAL DESIRED QUALIFICATIONS:

• Experience with physical modeling methods (e.g., molecular dynamics) and cheminformatics toolkits (e.g., rdkit)
• Previous focus on one or more of these areas: molecular property prediction, computational chemistry, de novo drug design, medicinal chemistry, small molecule design, self-supervised learning, geometric deep learning, Bayesian optimization, probabilistic modeling, statistical methods.
• Public portfolio of computational projects (available on e.g. GitHub).
  Job Type: Contract
  Pay: $66.69 - $75.00 per hour

Application Question(s):

• Only USC
• do you have an experience working in pharma industry

Work Location: In perso

• You will join Prescient Design within the Computational Sciences organization in gRED.
• Your peers will be machine learning scientists, engineers, computational chemists, and computational biologists.
• You will closely collaborate with scientists within Prescient and across gRED.
• You will develop machine learning and Bayesian optimization workflows to analyze existing, and design new, small and large molecules.
• You will be expected to form close working relationships with small molecule and protein therapeutic development efforts across the gRED organization.
• You will be expected to work on existing projects and generate new project ideas.