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-efficiency trade-offs, using automated configuration to find Pareto-optimal designs under real deployment constraints. 2) Build the distributed learning loop. Develop the learning and update mechanisms
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from working closely with its team of post-docs, associated researchers and partners (that range from Microsoft Research to the NHS). For this project you should have a strong interest in AI/Machine
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, using signal processing/machine learning techniques, to realise all-weather perception in autonomous vehicles with high-quality multiple-input-multiple-output (MIMO) radar sensing/imaging. The project
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PhD studentship in Machine Learning-Based MIMO Radar Sensing for All-Weather Perception in Autonomous Vehicles Award Summary 100% fees covered, and a minimum tax-free annual living allowance
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15th January 2026 Languages English Norsk Bokmål English English PhD Fellowship in molecular modelling and machine learning for improved subsurface utilization Apply for this job See advertisement
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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate
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, this PhD will explore machine-learning (ML) methods to significantly reduce the turnaround time of SRS, thus enabling their use for industrial design processes. By combining state-of-the-art numerical
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Are you interested in challenging deep learning at its core? And specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision
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administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate: 01.02.2026 | Working hours
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industrial Ph.D. position focused on developing scalable, Machine Learning (ML) pipelines for genomic and epigenomic biomarker discovery from Oxford Nanopore Technologies (ONT) long-read sequencing data