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following criteria: PhD in Computer Engineering, Computer Science, Electrical Engineering, or a closely related field Demonstrated research excellence, evidenced by peer-reviewed publications Expertise in
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Mechanical Engineering or Materials Science and Engineering (required for Ph.D. applicants) Experience with additive manufacturing, materials characterization, and/or physics-informed machine learning
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, AI and machine learning, robotics, engineering, computer vision, and signal processing. Details of this year’s workshop are at https://sites.google.com/view/telluride-2026/home IMPORTANT DATES
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the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD
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Job related to staff position within a Research Infrastructure? No Offer Description PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1
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. What you should have: A 1st degree in physics or engineering. An interest in optics, some ability in computer programming A desire to learn new skills in complementary disciplines. You will work jointly
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-resolution (SR) technologies influence human and machine-based facial identification. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: 1. Do SR
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BSM processes. This will involve taking a lead role in developing dedicated software frameworks, including the implementation of machine learning techniques. A long-term attachment (6-12 months) and
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application to: Prof Serkan Turkmen serkan.turkmen@taltech.ee Where to apply Website https://academicpositions.com/ad/tallinn-university-of-technology/2026/phd-posi… Requirements Research FieldComputer
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contribute 1) to the analysis methods and metrics for understanding the complex interactions between forage resource and dynamics; 2) to develop Machine Learning methods for analysing sensor data on animal