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enable the model to infer health-related information directly from NMR spectra of human blood. To this end, the model will be pre-trained using self-supervised learning on large-scale, partly synthetic
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) expect to appoint an experienced postdoctoral researcher in Fall 2025 (with flexible starting date). We are looking for an innovative experimentalist (m / w /d) with an established research track record
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on the cutting-edge field of Human-Centered AI Technologies using advanced Generative AI and novel interaction technologies such as VR/AR and Eye Tracking. PostDoc and PhD Positions in Human-Centered AI
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, adversarial attacks, and Bayesian neural networks. Excellent analytical, technical, and problem-solving skills Excellent programming skills in Python and PyTorch including fundamental software engineering
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Postdoctoral Position: Ph.D. in Robotics, Mechanical Engineering, Electrical Engineering, or a closely related field Proven research experience and publication track record in robotic manipulation, deformable
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required to create a holistic picture. Such additional information can improve the performance, help to reveal biases, or may enable to perform causal inference. We are interested in developing statistical
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knowledge in Machine/Deep Learning with experience in discriminative models, domain adaptation, and variational inference. Excellent analytical, technical, and problem solving skills Excellent programming
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the possibility of an extension. TASKS: Mathematical modeling and development of inverse methods (e.g. Bayesian inversion, optimization based methods, sparsity promoting methods based on L1-norm minimization and
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to lead a team of highly motivated scientists and engineers, from students to experienced scientists, in a structured and positive atmosphere. - You have a proven track record of acquiring and coordinating
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disciplines (typically mathematics, physics). For Postdocapplicants: Excellent track recordin computer science or engineering. Fluency in spoken and written English is required. Proficient in at least one