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science, preferably artificial intelligence, in research and teaching, and who complements and diversifies existing research strengths of the department. The new professor will teach in the Bachelor’s, Master's, and
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Immunology, Bioinformatics of Microbes and Microbiomes, Computational Pathology, Machine Learning/Deep Learning in Bioinformatic Data Analysis, Bioinformatics in Clinical Applications. The professorship will
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy
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program and facility. The successful candidate will add to this expertise and help build a new intersection of neuroscience and artificial intelligence. Modern machine learning and AI techniques now enable
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biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and epigenetic mechanisms
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) - Implement a demonstrator of the platform where a human learns how to operate a CNC machine with the help of a social robot, through the digital twins and interfaces. This includes: o Defining a learning
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implementing computational schemes for ODE and / or PDE based models Ideally experience with machine learning methods for identifying governing equations from experimental observations (e.g., https://github.com
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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scientific machine learning, knowledge of atmospheric dynamics, new observations, and close connections with national meteorological services, as well as several leading weather forecasting centers and tech
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research program in their field, as well as teach at the undergraduate and graduate levels. More information about the Physics Department and the Center for Quantum Phenomena can be found at https