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Field
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://www.academictransfer.com/en/jobs/355391/postdoctoral-researcher-machine… Requirements Specific Requirements You hold a PhD degree in Computer Science, Data Science, Biomedical Engineering, or a closely related field, with a
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Job related to staff position within a Research Infrastructure? No Offer Description Join a transformative project at RIBES using machine learning and genomics to overcome linkage drag and accelerate
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Image Analysis Group (DIAG) at Radboudumc. We develop, validate and deploy novel medical image analysis methods, usually based on the newest advances in machine learning with a focus on computer-aided
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electron ground states. Another promising route towards physical implementations of energy-based machine learning and neuromorphic hardware is to utilise material platforms that exhibit multiwell behaviour
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analytics, modelling, and AI to turn scientific research into real-world impact. You’ll join an open, supportive environment that fosters learning and professional growth. Job requirements Your profile: PhD
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) for engineering systems and structures, as well as expertise in machine learning, stochastic modeling, and Bayesian statistics. Programming Skills: Proficiency in programming languages such as Python, C, or R
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. You'll be part of the Tactile Machines Lab, which is a dynamic, interdisciplinary group of researcher bringing together expertise in robotics, sensing, machine learning, biomechanics, and haptics
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several key academic and industrial partners. You will be part of a diverse and passionate research team of academic staff, PhD candidates and Postdoctoral researchers in the Computer Engineering group
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part of a diverse and passionate research team of academic staff, PhD candidates and Postdoctoral researchers in the Computer Engineering group. Curious to learn more about the project, and perhaps our
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degree in engineering, mathematics, or a related field, with a strong background in prognostics and health management (PHM) for engineering systems and structures, as well as expertise in machine learning