Sabine Reichert
About Sabine Reichert
Sabine Reichert is the Principal Drug Discovery Scientist at BenevolentAI in London, with a proven track record of high-impact publications and extensive experience in supervising students and leading drug discovery projects.
Current Role at BenevolentAI
Sabine Reichert is currently employed at BenevolentAI in London, England, United Kingdom as a Principal Drug Discovery Scientist. In this role, she is involved in cutting-edge scientific research and employs advanced techniques to drive drug discovery initiatives.
Previous Positions
Prior to her current position, Sabine worked at BenevolentAI as a Senior Drug Discovery Scientist from 2019 to 2020. She has also held significant roles at various prestigious institutions, including a Sir Henry Wellcome Fellowship at University College London from 2015 to 2019, a Postdoctoral Research Fellow at University College London from 2014 to 2015, and a PhD student at Cancer Research UK from 2009 to 2014.
Education and Academic Background
Sabine Reichert has an extensive academic background. She earned a PhD in Developmental Cell Signalling from Cancer Research UK - London Research Institute (now Francis Crick Institute). She studied Biology and achieved a Diploma at Friedrich Schiller University Jena and also studied Physics there from 2002 to 2004. Additionally, she attended the University of Montpellier to study Biology.
Supervision and Mentorship
Sabine has significant experience supervising students at various career stages. Throughout her career, she has guided and mentored young scientists, helping them develop their research skills and scientific understanding.
Research and Publications
Sabine Reichert has a proven track record of high impact publications. Her research spans multiple fields including molecular biology, tissue culture, cancer biology, behavioural neuroscience, and drug screening. She is proficient in working with large data sets and has applied biomedical knowledge graphs and machine learning to hypothesis generation in Target ID.