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Field
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Qualifications · PhD or MD/PhD in neuroscience, molecular/cell biology, bioengineering, or a related field. · Demonstrated experience in extracellular vesicle exosome biology and advanced statistical analysis
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Science, or a related field. No experience required. Preferred Qualifications PhD in Computational Biology, Bioinformatics, or a related field (e.g. statistics, computer science, or quantitative biology
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, quantum science, condensed matter, materials, photonics and interdisciplinary applications of physical science. This role sits within a collaborative quantum science project at King’s on quantum algorithms
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects and mentoring. Contribute to academic publications
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elaborated an algorithm for identification of cancer specific T cells, which selectively kill autologous tumour but not healthy lung tissue. Simultaneously, we have developed the method for identification and
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. Responsibilities: Conduct research on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy
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, Algorithms, and Data" team at L2IT. Application procedure: Interested candidates must send: 1. A cover letter presenting their research project and their interest in joining the group 2. A Curriculum Vitae 3
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7 Jul 2026 Job Information Organisation/Company UNIVERSIDAD POLITECNICA DE MADRID Department HRS4R Research Field Computer science » Other Researcher Profile Recognised Researcher (R2) Positions PhD
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artificial intelligence and reinforcement learning approaches for image-guided vascular navigation. • Design experiments, validation strategies, and quantitative performance measures for navigation algorithms