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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The project aims to develop innovative services to optimise the management
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from multiple systems and sources to answer key operational questions. Deep experience using a variety of data mining/data analysis methods to build and implement dashboards, models and algorithms
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 9 hours ago
, investigating how the rapid adoption of AI is transforming work, and how algorithmic decision-making shapes markets; gain exposure to and training in a broad set of research topics in economics and computer
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of novel optimisation algorithms and the inclusion of richer sources of prior knowledge. You will be part of our bubbly, multi-disciplinary team that comprises both computational and wetlab scientists. You
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, Computer Science, Statistics, or other related fields. Familiarity with machine learning and signal processing algorithms for wireless communications. Good written and oral communication skills
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: Operational Research Applied Mathematics Computer Science Business Analytics A related quantitative field You will also bring experience in: Optimisation algorithms (exact methods and heuristics), Strong
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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 15 days ago
fundamental research across computational, physical, and social dimensions, we shape artificial intelligence and robotics to advance knowledge and benefit society. The Optics & Sensing Laboratory (OSLab
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28 Oct 2025 Job Information Organisation/Company University of Nottingham Research Field Engineering » Computer engineering Engineering » Control engineering Engineering » Electrical engineering
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Requirements REQUIRED: Ph.D. in computer science, mechanical engineering, applied math, or related field with significant research experience in machine-learning/AI algorithm development, specifically in deep
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proofs, bounds, convergence results) alongside algorithm design and high-performance computation. Biological case studies, such as slime mould experiments, serve as inspiration and as a unique source of