The Principal Scientist in Advanced Data Analytics (ADA) within our Quantitative Pharmacology (QP) organization is a strategic, scientific and cross-functional role of deploying and fostering next-generation model-informed drug development (MIDD) using ADA in order to increasingly take advantage of Real-World Data and support personalized medicine. This position will participate to QP activities to strengthen MIDD capabilities by developing and implementing ADA strategies/plans fully integrated into the overall preclinical and clinical plans across ourprojects and disease area. This position will be responsible for project-related Machine Learning (ML)/Deep Learning (DL) activities in QP either performed independently, under supervision and/or in collaborationwith external CROs or academic institutions
Requirements:
Ideally 5+ years (Bio)pharmaceutical industry and/or postdoctoral experiences with a doctorate (PhD, PharmD or MD) relevant in the related fields of Computer science, Mathematics, Engineering. Industry experience in Healthcare, Biotech or Biopharma R&D is an asset; Strong theoretical knowledge and multi-year hands-on experience state-of-the-art ML (supervised, unsupervised, reinforcement learning) and DL methods (RNN, CNN, ensemblemethods, transformers). Strong background in mathematics and statistics; Proficiency in programming languages like Python or R and full familiarity with ML/DL frameworks (Tensorflow, PyTorch, scikit-learn, Keras) and visualization libraries (Matplotlib, Seaborn, Bokeh). Hands-on experience in data cleaning, preprocessing and exploration tasks prior to data design
Text:
Principal Scientist in Machine Learning (m/f/d) The Principal Scientist in Advanced Data Analytics (ADA) within our Quantitative Pharmacology (QP) organization is a strategic, scientific and cross-functional role of deploying and fostering next-generation model-informed drug development (MIDD) using ADA in order to increasingly take advantage of Real-World Data and support personalized medicine. This position will participate to QP activities to strengthen MIDD capabilities by developing and implementing ADA strategies/plans fully integrated into the overall preclinical and clinical plans across ourprojects and disease area. This position will be responsible for project-related Machine Learning (ML)/Deep Learning (DL) activities in QP either performed independently, under supervision and/or in collaborationwith external CROs or academic institutions Ideally 5+ years (Bio)pharmaceutical industry and/or postdoctoral experiences with a doctorate (PhD, PharmD or MD) relevant in the related fields of Computer science, Mathematics, Engineering. Industry experience in Healthcare, Biotech or Biopharma R&D is an asset; Strong theoretical knowledge and multi-year hands-on experience state-of-the-art ML (supervised, unsupervised, reinforcement learning) and DL methods (RNN, CNN, ensemblemethods, transformers). Strong background in mathematics and statistics; Proficiency in programming languages like Python or R and full familiarity with ML/DL frameworks (Tensorflow, PyTorch, scikit-learn, Keras) and visualization libraries (Matplotlib, Seaborn, Bokeh). Hands-on experience in data cleaning, preprocessing and exploration tasks prior to data design
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