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reactions. Building upon recent advances such as plasma-directed relation graph techniques (P-DRGEP), principal component analysis, and machine-learning-based lumping strategies, the PhD candidate will
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Offer Description We are looking for a PhD student to join our Signal Theory and Statistical Learning group at TU Darmstadt, Germany. The position is in the mathematical foundations of deep learning, with
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cooling mechanisms and their corresponding refrigeration cycles. The project will integrate thermodynamic modelling, machine learning, and multi-objective optimisation to identify high potential
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employment. Required selection criteria You must have experience with computer vision and machine learning. You must have excellent programming skills in Python with exposure to popular deep learning libraries
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advanced machine learning feature detection to enable evolving subsea scenes to be robustly aligned across repeat surveys. You will develop probabilistic models to detect subtle changes under noise and
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for probabilistic unsupervised learning for structured biological data. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/307053/3-years-phd-position-in-probabilistic-machine
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. For more information about the network, consult https://divine.unimi.it/ What are you going to do You will: be affiliated with the AISSR and participate in its organized PhD training. The academic work is to
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Classification Title: RES AST SCTST Classification Minimum Requirements: PhD in Computer Science, Computer Engineering, Data Science, Artificial Intelligence, Machine Learning or a closely related
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that truly understands its environment. You have a master's degree in Computer Science, Artificial Intelligence or similar. You are interested in Logic, Machine Learning, Knowledge Graphs, Stream
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5th November 2026 Languages English English English We're seeking a PhD candidate in Biotechnology to tackle antimicrobial resistance. PhD in Bioinformatics and Machine Learning for Infection and