gRED AI - Scientist

United States of America, California, South San Francisco

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The AI Scientist will act as a tech lead and be required to establish and apply new AI methods to specific problem domains within those functions. This position requires the incumbent to leverage strong machine learning knowledge and hands-on experience for solving real AI problems. With the supervision and mentoring of the head of ECDi MLP, the AI scientist will develop and implement novel mathematical and algorithmic techniques for machine learning applications of ECD AI projects. There are two studies tracks that can be explored by the newly recruited AI Scientist. One is to apply and develop advanced machine learning/deep learning models to process protein’s amino acids sequence for TCR-antigen interaction prediction in cancer immunology and antibody design/engineer in protein science with varieties of protein-protein interaction scenarios, which can facilitate the drug discovery process in large molecule drug development and cancer immunology therapies. Meanwhile, the team is exploring a new direction of personalized medicine AI for oncology. The focus for this direction is to apply machine learning and deep learning approaches to incorporate genomic information, model and integrate patients biomarker/digital biomarker and EHR data from clinical trials to make multimodality predictions on the patients’ disease progression, response/non-response/survival rates, and accordingly help infer the decision for clinical scientist to design the clinical trials, with built-up AI products speeding up workflows within ECD. Furthermore, the analysis on the patients’ data can help conduct reverse translation study to guide drug/target discoveries in early research.

Responsibilities

  • Participate in cutting-edge research in machine intelligence and machine learning applications.

  • Act as an implementer to design and run experiments, including designing and evaluating new algorithms as well as implementing known algorithms.

  • Self-learn ad-hoc machine learning techniques for projects, but receive hands-on experience while working with some of the most esteemed AI Scientists in the industry.

  • Develop solutions for real world problems in clinical trials, drug/target discovery, and biomarker analysis.

  • Provide intellectual support to other MLP team members and share your knowledge and achievements within our MLP team.

Qualifications

  • PhD degree in Computer Science, Applied Mathematics, Bioinformatics, Computational Neuroscience/Biology or a related computational discipline, or equivalent combination of education and practical experience specializing in Artificial Intelligence, machine learning and deep learning.

  • Experience with applying machine learning and deep learning on omics, protein science or biomarker analysis for translational medicine is a big plus.

  • Experience with transfer learning, meta learning and multimodality predictive modeling is a big plus.

  • 3+ years of relevant professional or academic experience with a proven track record in machine learning or deep learning and software engineering.

  • Public and private repositories and a track record of contribution to an open source package.

  • Proficiency with programs such as Python, C++, Scikit Learn and PyTorch.

  • Strong analytical and problem-solving skills.

  • Excellent oral and written communication skills.

  • Ability to lead cross-functional multi-disciplinary teams.

  • Ability to work effectively in teams and collaborate with others to solve challenging business problems.

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