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Field
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) to develop accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models
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exploration and relevant disciplinaries Key Responsibilities: Develop novel imaging algorithms and validate them through synthetic experiments Extend these methods to real-world experiments to address practical
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16 Apr 2026 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique de Paris-Nord Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage
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approach makes it easier to identify different local optima using sampling mechanisms. In stochastic optimization, distribution estimation algorithms (EDA) are an alternative approach to traditional
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. The position will focus on developing computational algorithms and tools for the analysis of mass spectrometry-based proteomics data. Research projects will center on advancing the FragPipe computational
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on computer vision. The role will focus on developing, designing, and implementing novel algorithms and models to address emerging problems in computer vision, such as Multimodal Large Language Models and
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) experience in large model training, knowledge distillation or efficient deep learning algorithm development, foundation model implementation and optimisation; and (c) good communication skills in English
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position is available in the group of Prof. Alexey Nesvizhskii at the University of Michigan Medical School. The position will focus on developing computational algorithms and tools for the analysis of mass
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underwater robots. - Designing, implementing, and evaluating navigation, control, and mission planning algorithms. - Studying multi-robot coordination and human-robot teaming strategies. - Participating in
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collaborate closely with Professor Colin Meyer at Dartmouth College to develop new models of polynya dynamics, efficient algorithms for inversion of surface signatures, and deeper understanding of controls