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Field
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using deep learning, computational chemistry, medicinal chemistry, chemical biology, and molecular cell biology to develop novel therapeutics to tackle complex diseases such as cancers. Successful
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by developing a general mathematical theory of symmetries in BP and efficient algorithms for symmetry detection and exploitation. While the related field of mixed-integer programming (MIP) primarily
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-driven biomarkers Initial focus will be placed on projects designed to refine and validate artificial intelligence (AI) algorithms for analyzing OCT imaging in diabetic macular edema (DME). Data processing
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for real-time human data processing in interactive settings. Technical expertise in areas such as electrophysiological recording, VR paradigm design, closed-loop algorithm development, or clinical
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, understand the design and development decisions that propagate social biases, and develop theoretical and algorithmic approaches to mitigate them. Key responsibilities include developing bias detection tools
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, and uncertainty-aware algorithms for autonomous driving systems. The position focuses on developing robust decision-making, planning, and control methods that address uncertainty arising from perception
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by integrating large-scale single-cell foundation models with structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under
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AI Algorithm and Autonomous Decision-Making Systems RESPONSIBILITIES Research and develop autonomous decision-making algorithms for process industries (e.g., chemical, pharmaceutical, materials, energy
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farming, robotics, metrology, cultural heritage, and geomatics. The Data Science for Industry and Physics (DSIP ) Research Unit focuses on applying Data Science methodologies and approaches to develop
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properties of macromolecules, developing novel ways to combine quantum chemical methods and machine learning, developing quantum algorithms for computational chemistry on quantum computers, and applying