Scientist, Machine Learning Computer-Aided Drug Design
Developing innovative therapeutics to treat diseases like Alzheimer’s disease, various types of cancers, and infectious diseases like Hepatitis B, influenza is our mission. In this endeavor, we are seeking to recruit new talent for the comprehensive analyses of high-dimensional datasets using state-of-the-art data science methods applied to drug discovery programs. The position is opened at Spring House (PA), a headquarters of Janssen Research & Development. We significantly increased our investment into the workforce for data analysis pipelines with the emphasis in current cutting-edge technologies to support future Artificial Intelligence-driven drug design and discovery.
Janssen Research & Development L.L.C. has an open position for a full-time scientist to support drug design and discovery projects using machine learning approaches. We are looking for candidates with a track record in machine learning, strong coding experience and preferably experience working with chemical or biological data, but we are happy to teach chemistry and biology to everyone from different background and passion for complex data.
A candidate will develop prediction pipelines for small molecule compounds by integrating diverse data sources (chemical structure, microscopy images, gene expression) to infer biological activities of millions of chemical compounds, and to apply these predictions to drive drug design projects. Predictive pipelines aim to increase the safety and efficacy of the drug candidates and decrease the time needed to progress hit compound to lead compound to compound in clinical trials. Testing of them in real projects would require interaction with chemists, biologists, and data scientists and iterative model optimization if needed. The candidate will also be responsible for the integration of new machine learning pipelines, optimization of it, and deploying on current projects.
Additionally, the candidate will drive research in transfer learning with an emphasis on deep transfer learning. Deep learning and other multi-task machine learning techniques have already shown promise for small molecule projects in Janssen, yet most of those models require a significant amount of data, while many bioassays generate significantly smaller datasets that require transfer learning to integrate them successfully into the predictive pipelines.
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Johnson & Johnson is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
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