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1st February 2026 Languages English English Norsk Nynorsk English PhD Research Fellow in Algorithms and Extremal Combinatorics Apply for this job See advertisement UiB - Knowledge that shapes
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authentication modalities to develop more efficient and effective methods of generating biometric signatures of users. The newly developed modalities would rely on multiple user’s behavioral traits (e.g., typing
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 1 day ago
hospitalization (HH) services. The main objectives are to develop optimization models for staff scheduling that incorporate the distinctive characteristics of HH and address multiple objectives, and to create new
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We are seeking to appoint a talented Bioinformatician to join a team at a pivotal time where you will be developing a predictive algorithm for immunogenicity based off of biological mechanisms. In
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, focusing on the development of a mobile DC microgrid for military tactical applications. The role involves designing and implementing advanced control algorithms to coordinate multiple energy sources
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the Novo Nordisk Foundation, that will drive research and innovations at multiple levels - from developing scalable quantum processor technologies to solutions for the quantum-classical control and readout
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inference in engineered systems, including telecom networks; The development of neuromorphic algorithms and spiking neural models with built-in efficiency and reliability guarantees; The design of reliability
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institutions from academia and industry in multiple research projects. What you will do Development & application of innovative data analytical algorithms in medcine wieth specific focus on digital device
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, and/or applications of algorithms, methods, and software for data analysis. Responsibilities include querying databases, data cleaning and quality control, supervised and unsupervised machine learning
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algorithms and methods for calibrated Bayesian federated learning for trustworthy collaborative Bayesian learning on data from multiple participants. The project will develop new methods, theory, and