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Field
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large datasets, and applying AI approaches (e.g. machine learning, image segmentation, multimodal AI data integration) will be considered advantageous. Strong skills in communicating scientific results
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implementing signal processing algorithms specifically tailored to analyze signals that contain interfering impulsive content, often encountered in data coming from main and pitch bearings. Machine learning
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the application of machine learning (ML) methods or large language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g
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degree (or equivalent) in Data Science, Computational Biology, Bioinformatics, Computer Science, Physics or a related field Solid programming skills and knowledge in deep learning, statistical modelling
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geospatial workflows on an abstract level, using purpose-driven concepts and conceptual transformations; develop AI and machine learning based technology to automate the description and modeling of data
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recent large-scale capabilities in physics. Reliability, exploring uncertainty quantification and robust inference in machine learning. Explainability, leveraging identifiability and unique recovery
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Centrum Wiskunde & Informatica (CWI) has a vacancy in the Machine Learning research group for a talented PHD-studenT iN NeuroAI of Developmental vision (m/f/x) Job description A PHD-studenT iN
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for extracting physiological biomarkers from ECG, PPG, and related sensor data Machine learning and AI for predictive modelling and risk stratification Computational physiology modelling to personalise and
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and exact optimization methods enhanced by machine learning (ML). The overarching goal is to solve large-scale combinatorial optimization problems more efficiently, particularly in domains such as
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University of Vienna, the PhD program for life scientists and computational scientists/machine learning experts will start in January 2026. The goal of the PhD Program is to address real-world problems in