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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 17 days ago
the structure from such data is challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 6 hours ago
track-record in first-author scientific publications for Postdoc applications Experience with data-driven machine learning methods for modelling (PINN, Sparse Symbolic Regression methods) High willingness
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 20 days ago
to participate in one of several available PhD programs, with three years funding, in collaboration with the University of Göttingen. Masters students aiming at a fast track PhD are also welcome. The Postdoc
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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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programs, with three years funding, in collaboration with the University of Göttingen. Masters students aiming at a fast track PhD are also welcome. The Postdoc position is limited to two years with a
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 1 month ago
absorption spectroscopy (XAS) is a powerful method for understanding the structure of working functional materials and catalysts, and tracking their structural and chemical changes. XAS experiments
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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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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
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to revolutionize the research field in 3D learning. Research topics include: - Neural Rendering: 3DGS, NeRF, etc. - Generative AI: Diffusion, LLMs, GANs, etc. - 3D Reconstruction - SLAM / Pose Tracking (SfM, MVS
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D