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and deep learning-based digital twins. Stipend: The selected faculty participant will receive a monthly stipend commensurate with their institutional salary. Program Requirements: To document
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experience. Applicants who are in the process of completing a Ph.D. degree will also be considered. Desirable qualifications include physics deep learning, digital twin, smart and resilient infrastructure
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Job related to staff position within a Research Infrastructure? No Offer Description At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and
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Schemes of Service: Faculty Division: Business, Communication and Design Employment Type: Fixed Term At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical
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economy. As a postdoctoral researcher, you will unravel how silicon suppresses liquid copper infiltration at the atomic scale, using density functional theory-accurate machine-learned potentials and
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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry
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. in Computer Science or a closely related field, with research focus in Reinforcement Learning, Machine Learning, Embodied AI, or AI for Education. Strong background in deep reinforcement learning, with
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control or learned policies on physical robotic hardware. Background in modern robot learning and policy learning methods, with hands-on experience in deep learning and reinforcement learning frameworks
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: ● Applicants must have a PhD in Computer Science or related field, with no more than five years post receipt of the PhD. ● Experience in one or more ML domains, such as deep learning, reinforcement learning
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ML domains, such as deep learning, reinforcement learning, or human-centered ML. Proficiency in programming languages (e.g., Python) and ML frameworks (e.g., TensorFlow, PyTorch), with evidence in