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development. The developed algorithms will be compared to the current state-of-the-art in method development using samples provided by some of Flanders’ most demanding industrial chromatography labs. To cover a
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for a Home or Overseas student. Fee: Home and Overseas Duration *: 3 years 1st Supervisor: Dr Mehdi Safavi 2nd Supervisor: Prof Andrey Pavlov Opportunity Reference No: CRAN-0069 Main Content
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reinforcement learning methods can be used to solve multiobjective discrete and combinatorial optimization problems. The goal is to develop new algorithmic approaches that combine ideas from machine learning
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microscopy is often limited by slow acquisition speeds and large volumes of redundant data, restricting its applicability in real-world scenarios. The goal of this PhD project is to develop a snapshot spatio
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, immunology, and allergology to better understand the interaction between airway epithelium and mast cells within healthy and diseased airways, identify biomarkers, and develop algorithms for the diagnosis and
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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PhD working with Prof. Hendrik Blockeel and/or Prof. Jesse Davis on analysis of time series data. The goal is to develop algorithms for detecting anomalies, discovering “motifs” (repeating patterns
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The Fraunhofer Institute for Algorithms and Scientific Computing SCAI in Sankt Augustin, near Bonn, has around 180 employees who research and develop innovative methods in the field of computational
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) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research sits at the intersection of AI Safety and
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of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research sits at the intersection of AI Safety and Data-Centric AI. We aim to make large