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marketing strategy, supply chain and logistics, digital distribution, and operations research. Leveraging the latest technologies, such as artificial intelligence, machine learning, and large language models
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the interplay between mutations, energetics, and evolutionary constraints, including epistatic effects. · Developing or applying machine learning approaches to predict or redesign frustration patterns in proteins
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We are seeking creative and energetic candidates with strong experience in multimodal machine learning and human behavior analysis and modeling for a one-year Postdoctoral position. Using recent
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data output by using appropriate computer language/tools to provide technical solutions for moderately complex application development tasks. Document code and associated processes by adhering
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, or R&D environment. Experience developing CAD models and generating CAM toolpaths for CNC machining of metals and plastics. Experience performing assembly and testing of experimental equipment
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for this position, the following is required: PhD in data or computer science, machine learning, AI, statistics, mathematics, biophysics, bioinformatics. Additional requirements In addition to your CV and your
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Qualifications: M.S. (or equivalent professional degree) in physics or a related field, and experience with different computer environments and languages especially Python, Matlab, IDL, FORTRAN and UNIX/LINX
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights
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Systems at The Technical Faculty of IT and Design invites applications for PhD stipends or integrated stipends in the field of Machine Learning for Intelligent Hearing Assistance in Complex Acoustic
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structure-preserving, machine learning–accelerated scientific computing for plasma physics applications. In particular, the project involves developing data-driven collisional kinetic models and numerical