14 parallel-computing Postdoctoral scholarships at Technical University of Munich in Germany
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18.09.2024, Academic staff We have several 𝐏𝐡𝐃 & 𝐏𝐨𝐬𝐭𝐃𝐨𝐜 𝐨𝐩𝐞𝐧𝐢𝐧𝐠𝐬 in our Visual Computing & AI Lab in Munich! Topics have a strong focus on GenAI, including 3DGs, NeRFs, Diffusion
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., for quantum computing, microfluidics, or conventional circuits and systems. Our focus on interdisciplinary partnerships and networks will enable you to meet many interesting people (at places all over the world
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(especially LLMs / VLMs) Human-AI Interaction Or Bring-your-Own research topic Who We Are Looking For: We seek highly motivated and talented individuals passionate about AI, Human-Computer Interaction, Eye
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for an interdisciplinary “bridge-builder” who strives for Scientific Excellence and Real-World Purpose. ● Background: HCI (Human-Computer Interaction), Computer Science, Ethnography, Sociology, or a related
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Equations Requirements: - Master’s / PhD degree in physics, mathematics, computer science, meteorology, or a related field - Excellent skills and strong background in programming (Python and Julia
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/264ffa19ca70e3ec41032fe6a4802932b5eda4e6.pdf https://ieeexplore.ieee.org/document/10068193 Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines (typically
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parameters are tuned so that the over-approximation of the computed reachable set is small enough to verify a given specification. We will demonstrate our approach not only on ARCH benchmarks, but also on
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questions. The advertised positions will be part of the project “QS-Gauge: quantum simulation of lattice gauge theories”, funded by the Emmy Noether programme of the DFG. The project’s overarching goal is the
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22.03.2021, Academic staff The 3D AI Lab at the Technical University of Munich is looking for highly motivated PhD students and PostDocs at the intersection of computer vision, machine learning, and
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
of such systems, taking particularly into account model uncertainties as well as limitations pertaining to acquisition of data, communication, and computation. We apply our methods mainly to human-robot-teams