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(+/–) applied to the electrodes can be optimised in a machine-learning approach to optimise the gel morphology and the embedded stimuli-transduction pathways towards the targeted mechanical behaviour. Departing
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adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases and in particular the complications encountered in photometric
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statistical methods; will seek out and learn new methods to better solve problems > Experience with modern AI techniques and methods or desire to work on Applied Machine Learning Problems > Constantly questions
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a PhD candidate in Robot Planning and Learning, you will become part of a dynamic, interdisciplinary research environment at the forefront of AI and Robotics. Our lab focuses on developing intelligent
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machine learning, with the goal of revealing how genome architecture shapes physiology, ecology, and evolution. Unlock hidden biological patterns while developing key computational and academic skills. Your
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learning approaches and contributing to the development of better (bio)catalysts and drugs? We are offering three fully-funded, 4-year PhD positions at the University of Groningen or the Technical University
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Apply now The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) is looking for a: PhD Candidate on Exploring Pareidolia in Computer Vision to Enhance Interpretability
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Apply now The Faculty of Science, Leiden Institute of Advanced Computer Science, is looking for a: PhD candidate for End-to-End Causal Learning (1.0 fte) Project description Causal inference is one
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implications. This PhD project offers a unique opportunity to work in an international environment in one of the biggest International Relations Department all over Europe and to acquire valuable research and
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one of the biggest International Relations Department all over Europe and to acquire valuable research and teaching experience. The two main supervisors of the PhD project are Matteo CM Casiraghi and