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optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically in AI-driven
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, agent-based models, network models, stochastic systems, or dynamical systems Experience with R or Python Experience working in high-performance computing environments Familiarity with version control
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interactive user-facing systems. The role includes support for integration, development, deployment, maintenance, UI/UX, containerization, automation, and system-level optimization. Please contact Jess
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prototyping & technologies such as stereolithography, two-photon printing or nano-imprint lithography is highly desirable Experience with scientific computing and optimization frameworks (e.g
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University of Luxembourg Location Luxembourg, Esch-sur-Alzette Salary Negotiable Closing date 2 Nov 2026 View more categories View less categories Discipline Computing Job Type Postdoctoral Employment
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(NUS), and BEARS. The role will focus on developing and implementing AI/ML-driven high-throughput, closed-loop experimentation for the discovery and optimization of electrocatalytic materials for CO
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development activities within the Biosciences Center by developing advanced metabolomics and photophysiology tools for cell biochemistry manipulation optimization for both biofuel and bioproduct
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Associate (PDRA). The appointed candidates will support advanced research initiatives focusing on systems design, distributed systems, and algorithmic optimization. Key duties involve driving foundational
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with advanced characterization tools (e.g., PPMS, XRD, SQUID magnetometry, optical spectroscopy, or scanning probe microscopy). Experience with high-performance computing or cloud-based machine
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segmentation algorithms, refinement of anatomical geometries, and optimization of surface and volumetric meshes. The fellow will also develop and evaluate multiphysics computational models coupling microwave