62 parallel-and-distributed-computing-"Multiple" positions at Nature Careers in France
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cross-disciplinary research programme in molecular structural biology, addressing key questions in RNA and infection biology, eukaryogenesis, and the muscle cytoskeleton. The Unit's research efforts focus
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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learning, focusing on identifying abrupt shifts in the properties of data over time. These shifts, commonly referred to as change-points, indicate transitions in the underlying distribution or dynamics of a
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statistics and machine learning, focused on identifying abrupt shifts in the properties of data over time. These shifts, known as change-points, indicate transitions in the underlying distribution or dynamics
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file named in the following format: LAST NAME of the candidate_Last Name of the supervisor_2023.pdf Description of the topic: Federated learning (FL) enables multiple stakeholders to collaboratively
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is replaced by multiple objectives or by satisfactory balance between different criteria. References [1] J. A. Bærentzen, J. Gravesen, F. Anton, and H. Aanæs, Guide to Computational Geometry Processing
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multiple tensor modeling: Several data modalities, including invasive (intracardiac electrograms, electroanatomic maps) and noninvasive (ECG, echocardiography), are acquired in the management of persistent
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within a coherent computational model is currently challenging, due to the typical large dimension and complexity of biomedical data, and the relative low sample size available in typical clinical studies
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malignancies, such as Multiple Myeloma and Mantle cell lymphoma. To uncover vulnerabilities within the tumor ecosystem, we combine fundamental and translational approaches, working closely with the University
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fields for several applications in the field of computer vision and inverse problem [SLX+21]. As far as the modeling of data term between distributions is concerned, one idea would be also to follow