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Your profile PhD applicants must possess a Master's degree in mathematics, theoretical physics, or computer science. Candidates should have an exceptional academic record and a robust mathematical foundation. While research experience is advantageous for PhD applicants, it is not...
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related to staff position within a Research Infrastructure? No Offer Description PhD Position in Decentralized Resource-Constrained Machine Learning The Distributed Computing (DISCO) Group is a research
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techniques in VLBI. The primary objective is to develop and apply novel strategies based on AI/machine learning (ML) to enhance VLBI data analysis and simulation. Specific tasks include: Designing and training
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Your position Our group conducts research at the intersection of artificial intelligence (AI) and pediatric healthcare, developing AI and machine learning (ML) methods to address real-world clinical
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such as autonomous cars and robots. Job description We have multiple open PhD positions at AVI@PRS and we are looking for motivated candidates with a strong background in computer vision, machine learning
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willingness to learn A solid foundation in experimental research, data analysis, and scientific methods Interest in machine learning and data-driven approaches to materials discovery Strong interest in hands
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velocity changes at selected locations with the introduction of unsupervised machine learning and study the interaction of mass balance changes (crustal stress changes) and geohazards such as rain-induced
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these projects will bring forward the integration of novel methods at the intersection of advanced control, optimization, manufacturing science, robotics, and machine learning. The two doctoral student positions
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at international conferences and workshops. Contribute to lab activities and brainstorming sessions. Stay updated with advancements in HCI, machine learning, and sensor systems. Profile We are seeking a motivated
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scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Required Skills: Strong analytical background Proficiency in geometric deep learning and machine learning Prior experience in physics-informed