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Principal Scientist - CADD AI Application Specialist ai-jobs.net

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At UCB, we put our heart, soul and skills into making a difference for people living with chronic disease. Working together to push the boundaries, we blend the best of our talents to unlock innovation. We are seeking a top class candidate to join our Computer-Aided Drug Design (CADD) team within Global Chemistry to drive the application of artificial intelligence and advanced machine learning technologies in small molecule drug discovery. The successful candidate will have solid understanding of small molecule drug discovery, computer-aided drug design, and applications of AI and advanced machine learning algorithms to address challenges in chemistry. This position can be located either in our UK offices in Slough or in our Belgian offices in Braine-l'Alleud.


A Career Unfolds in Phases

Communications of the ACM

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School of Science appoints 14 faculty members to named professorships

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The School of Science has announced that 14 of its faculty members have been appointed to named professorships. The faculty members selected for these positions receive additional support to pursue their research and develop their careers. Riccardo Comin is an assistant professor in the Department of Physics. He has been named a Class of 1947 Career Development Professor. This three-year professorship is granted in recognition of the recipient's outstanding work in both research and teaching.


Genenerative AI Models In Small Molecule Drug Discovery: The Open Challenge To Create A Unified Benchmark

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Generative AI models in chemistry are increasingly popular in the research community, mainly, due to their interest for drug discovery applications. They generate virtual molecules with desired chemical and biological properties (more details in this blog post).


Deep Dive Into Big Pharma AI Productivity: One Study Shaking The Pharmaceutical Industry

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The pharmaceutical business is perhaps the only industry on the planet, where to get the product from idea to market the company needs to spend about a decade, several billion dollars, and there is about 90% chance of failure. It is very different from the IT business, where only the paranoid survive but a business where executives need to plan decades ahead and execute. So when the revolution in artificial intelligence fueled by credible advances in deep learning hit in 2013-2014, the pharmaceutical industry executives got interested but did not immediately jump on the bandwagon. Many pharmaceutical companies started investing heavily in internal data science R&D but without a coordinated strategy it looked more like re-branding exercise with the many heads of data science, digital, and AI in one organization and often in one department. And while some of the pharmaceutical companies invested in AI startups no sizable acquisitions were made to date.