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contributions in one or more of the following key areas: computational modeling of chemical systems, AI-driven materials discovery/design, robotics for chemical synthesis, machine learning applications in
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(viability, proliferation, outgrowth, and invasion assays) is desirable. Experience with, or interest in, machine learning for the analysis of microscopy data and a strong ability to collaborate with
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the following areas desirable but not essential: electrocatalysis, rheology, coating technology, machine learning Intrinsic motivation to show initiative, creativity, and to work independently Excellent
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data set (e.g. neutron irradiations, that take years/decades to generate). Digilab brings AI/ML (artificial intelligence / machine learning) approaches for data engineering and automation to utilise
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(1–4) and in related projects. We encourage potential PhD candidates to visit our webpage to learn more about the research we are conducting. The PhD candidate is expected to be enrolled in two
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will also profit from the vibrant research community around machine learning of the SCADS.AI center (https://scads.ai ) and the recently granted Excellence Cluster REC² – Responsible Electronics in
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Fellow) PhD in Computer Science or a related field (Research Engineer) Bachelor/Master degree in Computer Science or a related field Proven ability to conduct independent research with a relevant
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software engines into a unified DAT toolchain, ensuring compliance with industrial EDA standards. Job requirements MSc or PhD in Electrical Engineering, Computer Engineering, or a closely related field
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deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an interest in their application to embodied systems. What
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postdocs, tenure-track positions, tenured positions, and positions for distinguished professorship. Candidates in areas including, but not limited to, Quantum Algorithms, Quantum Machine Learning, Quantum