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Job Description The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we are seeking a highly talented and motivated PhD student
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system or electrochemical system PhD in Chemistry/Materials Science/Physics Encourage initiating activities on MOF development, devising, and analytical process Experience in machine learning will be
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system or electrochemical system PhD in Chemistry/Materials Science/Physics Encourage initiating activities on MOF development, devising, and analytical process Experience in machine learning will be
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system or electrochemical system PhD in Chemistry/Materials Science/Physics Encourage initiating activities on MOF development, devising, and analytical process Experience in machine learning will be
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will investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable
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empirical, machine-learning, and physics-informed approaches for retrieving breaking-sensitive metrics from SAR and linking them to wave dissipation estimates derived from collocated sea-state information
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equivalent experience in machine learning or a related quantitative field (Computer Science, Artificial Intelligence, Statistics, Mathematics, Physics, Computational Biology/Chemistry). Candidates will be
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Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH | Barcelona, Cataluna | Spain | 5 days ago
machine learning techniques and minimizing the environmental impact of the solutions developed. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for-recruitment-of-pdi-postdo
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CFM-Centro de Física de Materiales/MPC-Materials Physics Center | Donostia-San Sebastian, Pais Vasco | Spain | about 2 months ago
to establish a closed-loop platform that combines computational inverse design, robotic synthesis, online characterization, and machine learning-driven optimization of plasmonic nanoparticles. Join us
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fields (PhD is preferred) and have a background in imaging, image analyses, machine learning, and software engineering. References: (1) A. J. Brooks et al, “Neutron interferometry detection of early