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, ultimately, predictable by machine learning. Specifically, you will build a first-in-class framework to expedite the design of high-affinity binders that engage with therapeutic targets or efficient (bio
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. Research methods include computational modelling, brain imaging (fMRI), machine learning, behavioural methods, and other techniques. Virtually everything we sense, think and do is uncertain. For instance
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, making AI-driven teamwork more intuitive and effective. This PhD offers an exciting opportunity to work at the intersection of Interaction Design (IxD), Human-Computer Interaction (HCI), and Artificial
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for this position will have the following qualifications/qualities An MSc degree in chemistry or a related field. Very strong academic performance. Experience in molecular machine learning. Experience with
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, machine learning, and latest state-of-the-art biochemical analysis tools. You will explore how active enzymes drive cytoplasmic motion and how this influences cellular function and life itself. This is a
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research area. Prior experience working with Neural Radiance Fields or Gaussian Splatting. Prospective applicants should have a strong academic record with a solid background in Machine Learning (Deep
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strong academic record with a solid background in Machine Learning (Deep Learning, generative models, diffusion models). Knowledge in sensor data processing and radaris a plus. Good programming skills
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Job related to staff position within a Research Infrastructure? No Offer Description How can we design new Human-AI interactions that enhance collaboration between people? This fully funded PhD explores
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Website https://www.academictransfer.com/en/jobs/350125/phd-candidate-in-causal-learnin… Requirements Specific Requirements You are/ You have: a MSc degree in statistics, machine learning, data science or a
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will have the chance to use cutting-edge techniques, including super-resolution microscopy (PALM, Smdm), single-particle tracking, machine learning, and latest state-of-the-art biochemical analysis tools