Florian Rohrer
About Florian Rohrer
Florian Rohrer is a Senior Computational Researcher at Exscientia, specializing in drug discovery through computer vision and machine learning. He has a strong academic background in Medical Informatics and Software Engineering, holding multiple degrees from prestigious universities.
Work at Exscientia
Florian Rohrer has been employed at Exscientia since 2022, currently holding the position of Senior Computational Researcher. His role involves utilizing advanced computational techniques to support drug discovery initiatives. Prior to his current position, he served as a Computational Researcher at Exscientia from 2019 to 2022, where he contributed to various projects focused on enhancing the efficiency of drug development processes.
Education and Expertise
Florian Rohrer has a strong educational background in medical informatics and software engineering. He earned a Master of Science in Medical Informatics from the Medical University of Vienna, completing his studies from 2014 to 2017. Additionally, he holds a Bachelor of Science in Software & Information Engineering from Technische Universität Wien, which he completed from 2009 to 2013. He further pursued a Master of Science in Software Engineering & Internet Computing at the same university, studying from 2013 to 2018. Currently, he is studying Informatik at the University of Zurich.
Professional Background
Florian Rohrer has accumulated diverse experience in the field of data science and research. He worked as a Data Scientist at pmOne Analytics GmbH from 2017 to 2019, where he applied analytical skills to various data-driven projects. Prior to that, he served as a Research Assistant in the Department of Epidemiology at the Medical University of Vienna from 2015 to 2017. His background includes a focus on computer vision and machine learning tools, particularly in applications related to drug discovery.
Technical Skills and Tools
Florian Rohrer specializes in the application of computer vision and machine learning techniques within the context of drug discovery. He works extensively with high-content data derived from fluorescence microscopy imaging, leveraging these tools to enhance the understanding and development of new therapeutic agents. His expertise in these areas supports the advancement of computational methodologies in pharmaceutical research.