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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame factorization methods
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2 Mar 2026 Job Information Organisation/Company Iquadrat Informatica SL Department Research&Development Research Field Engineering » Communication engineering Researcher Profile First Stage
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, enthusiasm for technology and the drive to adopt new skills and extended responsibilities. We offer an open, international team with flexible work organization and support of individual development. The group
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project NICE is a center for research-driven innovation (i.e., an SFI ) in which NTNU, the University of Oslo, and key industry players work together towards developing the knowledge and technology required
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1 will focus on developing new graph-theoretic frameworks for analyzing graph learning models, such as Graph Neural Networks or Graph Transformers. PhD position 2 will focus on designing scalable
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myocardial infarction or stroke. To better understand the development and progression of vascular disease, over the past decades we have, together with the Vascular Surgery Clinic, Karolinska Hospital
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for image classification and other domains against existing open source LLM (e.g., Llama 3, Phi-3), as well as develop new kinds of attacks, for example based on evolutionary algorithms. 2. Investigate
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
distribution. The work also aims to improve inference efficiency by reducing dimensionality, reusing computations, and combining multiple measurements. The PhD candidate will develop, test and validate
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packages to estimate variance components and/or in R; a desire to further develop advanced computational, modelling and algorithmic research skills, and utilize these developments into practical breeding