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High Wycombe, Buckinghamshire, United Kingdom, Leiden, Netherlands, Leiden, South Holland, Netherlands, Mechelen, Antwerp, Belgium, Zug, Switzerland Job Description: Postdoctoral Scientist - AI/ML for Drug Design - Data Sciences Analytics & Insights, Data Sciences,
Johnson & Johnson Innovative Medicine Johnson & Johnson Innovative Medicine is recruiting for a
Postdoctoral Scientist - AI/ML
to help advance AI/ML for Drug Design. The primary location for this position is High Wycombe, UK, or in Switzerland, Netherlands, Belgium, Germany and France, with up to 10% travel. Remote working options will be considered on a case by case basis. At Johnson & Johnson Innovative Medicine, we are working to create a world without disease—transforming lives by finding new and better ways to prevent, intercept, treat and cure disease. We bring together the best minds and pursue the most promising science. We are Johnson & Johnson Innovative Medicine. We collaborate with the world for the health of everyone in it. The Data Science Analytics & Insights team within Johnson & Johnson Innovative Medicine develops innovative solutions using a variety of data sources across multiple different disease areas, encompassing oncology, cardiovascular and metabolic disorders, immunology, neuroscience, and infectious disease. We are looking for a highly motivated and innovative Postdoctoral Fellow who will work at the intersection of AI/ML and Drug Design. Key Responsibilities:
Conceive, develop, and implement AI/ML solutions applied to drug design problems, including but not limited to, molecule structure generation/prediction and molecular property prediction, to help identify molecules that have the potential to become effective drugs Work closely with a cross disciplinary team of AI/ML scientists, imaging experts, structural biologists, and computational chemists to design and implement computational approaches, analyze and interpret results, and communicate findings through internal presentations, conferences and scientific publications Participate in cross-functional collaborations with external companies, academia, and internal scientific and data science teams Extensive hands-on coding and actively contribute to platform development Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making findings through peer-reviewed publications and/or scientific conferences Qualifications
Ph.D. in EE/CS/Statistics/Applied math or related majors Deep expertise in causality, such as causal discovery, causal representation learning; and/or Bayesian experimental design, such as Bayesian optimization, active learning Strong background in one or more probabilistic models, such as Gaussian processes, Bayesian deep learning, dynamical systems Track record of publications on top machine learning conference, e.g., ICML/NeurIPS/ICLR/AISTATS/UAI and statistical journals Proficiency with one or more programming languages such as Python or C++. Proficiency in one or more AI frameworks such as PyTorch or Tensorflow Excellent written and verbal communication skills Ability to work independently and as part of a team Familiarity with and exposure to drug discovery and clinical development processes is a plus Hands-on technical data analysis, cloud computing (AWS, Azure), and dockerization is a plus Training Opportunities:
Gain experience working in the pharmaceutical industry Navigate and work within a matrix environment Communication and presentation skills to clearly articulate results and impact to diverse audiences and partners through internal presentations, conferences, and scientific publications For additional general information on company benefits, please go to: https://www.careers.jnj.com/employee-benefits
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