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Prof. Igor Zozoulenko). Our focus is on: Machine-learning accelerated materials simulations ML-accelerated simulation of ion and charge carrier transport in energy materials Multiscale modeling
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of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine learning in general. OCBE
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consensus. The successful candidate will develop the algorithmic foundations of this framework—making the motion-generation stack modular and heterogeneous (combining model-based control with learning-based
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Join the Responsible Machine Learning (ML) 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
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artificial intelligence and machine learning (AI/ML) models that predict therapeutic response, identify clinically actionable patient subgroups, and support personalized treatment strategies. Through
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signals, imagery, and natural language, via adaptive machine learning; 2) Personalization of sequential decision making, biophysical digital twins, and the operation of digital and physical systems; and 3
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for Technology, Economics, and Development (CTED) with a primary focus on artificial intelligence, machine learning, mathematical modeling, and computational analysis. The Associate Research Scientist will play a
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evidence to support the evaluation of AI and machine learning models. This may include investigating data-centric AI strategies, such as data quality assessment, annotation refinement, dataset curation, and
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the implementation of optimal treatments on-the-fly; implementing representation learning and text-as-data pipelines, employing learned representations of complex data for downstream (econometric) models; working
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. Duties/Responsibilities: 1. Data Management, Review, & Analysis (70%) Advanced Neural Signal Processing: Apply quantitative analysis, signal processing, and machine learning methods to high-dimensional EEG