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Senior Machine Learning Researcher at Deep Origin. Deep Origin.  is a biotechnology company accelerating drug discovery through AI-powered tools. Our platforms simplify R&D, simulate biology, and empower scientists to solve diseases and extend healthspan.. We are looking for a Senior ML Engineer with experience in creating predictive models, particularly in the biology space. You will help to create ML-based representations of specific biological systems, as well as take part in tuning and optimization of larger composite models, with the goal of creating a multiscale biological simulator for drug response prediction. You will also work with the Cellular Simulations team to incorporate biological simulations and mechanistic insights into the ML-based approaches.. B.S. or M.S. in a relevant quantitative field (Computer Science, Math, Physics, etc.).. . At least 5 years of experience in the development of machine learning models in an industry setting.. . Knowledge of optimization methodologies for machine learning models.. . Extensive coding experience, preferably Python, but other language proficiency will be considered depending on experience.. . Fluent English for collaboration with an international team. . . Nice to have:. . Ph.D. in relevant field.. . Deep experience in biological modeling and simulation, in particular in a systems biology or molecular level context.. . Experience with ML tasks involving small datasets.. . Experience in optimization of “composite models” - connected models that share output/input.. . Responsibilities. . Construct ML-based representations of biological systems, in particular signaling pathway dynamics in cells. . Help to create a hybrid multiscale biological simulator, incorporating ML components for more effective model calibration and simulation. . . Plan and organize work to ensure specific deadlines and milestones are met, coordinating with others to ensure work is correctly aligned and integrated with other efforts. . . Communicate effectively within the company and external teams, updating others frequently on progress and bottlenecks. . . Company Location: Portugal.