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Field
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Experience in devising and developing novel machine learning algorithms Hands on experience with ROS and physical robots Excellent mathematics skills, particularly in areas relevant to robotics and AI
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checks that comply with IRB/ethical standards. Design and implement computer-vision algorithms. Develop, test, and refine deep-learning models (e.g., detection, segmentation, tracking) in PyTorch
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work independently on complex projects. Experience and Education Master’s degree in Software and Computer Engineering (French engineering schools are preferred). Experience in optimizing ML algorithms
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(OTUs) in microbial communities using graph theory and the Slope-Matrix-Graph (SMG) algorithm. The student will be actively involved in algorithm design, data analysis, and result presentation, gaining
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are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources for end-to-end
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AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical imaging QUALIFICATIONS Successful applicants will have: a PhD in
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-fostering prototypes through co-design with children, creating evaluation frameworks to assess children's algorithmic agency in educational contexts, and establishing design principles that prioritize
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and computing, to apply. One position will focus on the scaling, calibration, operation, and tuning of spin qubit arrays using algorithmic techniques, as part of an international project, with
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algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software
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-disciplinary research environment Desirable criteria 1. Experience in devising and developing novel machine learning algorithms 2. Hands on experience with ROS and physical robots 3. Excellent