Machine Learning Scientist - Small Molecule Drug Design

ppBei Roche kannst du ganz du selbst sein und wirst für deine einzigartigen Qualitäten geschätzt. Unsere Kultur fördert persönlichen Ausdruck, offenen Dialog und echte Verbindungen. Hier wirst du für das, was du bist, wertgeschätzt, akzeptiert und respektiert. Dies schafft ein Umfeld, in dem du sowohl persönlich als auch beruflich wachsen kannst. Gemeinsam wollen wir Krankheiten vorbeugen, stoppen und heilen und sicherstellen, dass jeder Zugang zur Gesundheitsversorgung hat – heute und in Zukunft. Werde Teil von Roche, wo jede Stimme zählt. /p h3Die Position /h3 pJoin the small-molecule team within AI for Drug Discovery (AI4DD), formerly Prescient Design, at Roche and Genentech’s Computational Sciences Center of Excellence as a Machine Learning Scientist / Senior Machine Learning Scientist in Small Molecule Drug Design. You will develop and apply ML methods and models to accelerate small-molecule drug design with a focus on structure-driven approaches, working hand in hand with world‑class computational and medicinal chemists and structural biologists. /p h3The Opportunity /h3 ul libDesign, build, and apply cutting-edge ML models /b for small-molecule drug design, focused on protein–ligand interactions, binding affinity and key molecular properties. /li libTrain and fine-tune foundation models /b for structure prediction, using internally developed and open-source models on internal datasets. /li libValidate and refine ML-generated hypotheses /b alongside world‑class computational and medicinal chemists and structural biologists. /li libDrive scientific impact /b through publications, open-source releases, and conference talks. /li libCollaborate widely /b with computational and experimental researchers at Roche and with academic partners. /li /ul h3Who you are /h3 ul liYou bring deep machine-learning expertise with a strong foundation in linear algebra, probability and optimization, and hands‑on experience designing implementing machine learning approaches such as graph neural networks, sequence models, and reinforcement learning. /li liYou have structure-driven modelling experience with co‑folding methods, binding‑affinity prediction, and structural‑biology datasets. /li liYou are fluent in Python and cheminformatics with toolkits such as RDKit and OpenEye, and modern ML frameworks like PyTorchor JAX. /li liYou hold a PhD or equivalent research depth in machine learning, computational chemistry, chemical engineering or a related quantitative field such as physics or statistics. /li liYou have a record of scientific excellence evidenced by journal and conference publications or a public portfolio of relevant projects (e.g. hosted on GitHub/GitLab). /li /ul h3Preferred: /h3 ul liHands‑on experience building structure‑prediction foundation models. /li liExperience collaborating directly with medicinal chemists and structural biologists. /li /ul h3Location Travel Requirements /h3 pThis position must be based in either Basel, Switzerland (preferred) or Welwyn Garden City in the United Kingdom. Although this can be a hybrid role, there is an expectation of ongoing and sustained site presence, in compliance with local company site requirements. /p pIf using AI to design the medicines patients need next inspires you, apply now and help accelerate small-molecule discovery at Roche. /p pWhere pay transparency applies, details are provided based on the primary posting location. For this role, the primary location is Basel. If you are interested in additional locations where the role may be available, we will provide the relevant compensation details later in the hiring process. /p pbRoche ist ein Arbeitgeber, der die Chancengleichheit fördert. /b /p /p #J-18808-Ljbffr