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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
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engineering the LPC process for emerging applications. Aim and Objective In this project, we define LPC as the unifying theme for different non-related emerging applications. We will conduct a systematic study
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. The ideal candidate will have: • A Ph.D. in urban studies, geography, architecture, or a related field. • Extensive experience in ethnographic and qualitative research methods. • A proven track record of
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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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candidate will show in-depth methodological and applied knowledge in the field of machine learning, especially deep learning, experiences in the area of uncertainty quantification, generative and Bayesian
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or equivalent in one of the following: law, and or/ ethics or other relevant field is required. Key Responsibilities Conduct research as outlined in the project’s objectives under the supervision
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motivated PhD students to strengthen our interactive and collaborative team. The projects are founded on the well-established and highly visible track record of the laboratory in the analysis of plant growth
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fast response, new sensing-electrode chemistries, and an expanded scope of gases. The objective of the proposed PhD project is to investigate new materials, manufacturing routes and devices as