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1-year fellowship in Shoebill Conservation Genetics with support for a further 3-year PhD fellowship
biology, or conservation completed before 31 July 2026. In addition to an interest in evolutionary and conservation biology, the candidate should be committed to doing field work, wet-lab work, learning
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of blockchain, post-quantum cryptography, quantum algorithms, and heterogeneous quantum computing. Specifically, to achieve the main goal the project is expected to focus on three main areas: How can we support
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-edge optical microscopy systems for biomedical applications. This project involves the development of compact, label-free quantitative tomography systems and inverse scattering algorithms to push the
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, in collaboration with the team responsible for the development of the ApneaScreener algorithm. Knowledge of data analysis tools, particularly Python and R, will be valued to support the interpretation
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 29 days ago
, financed by EU and national funds through FCT/MCTES (PIDDAC Workplan: Machine learning algorithms, in particular deep learning ones, suffer from the phenomena of catastrophic forgetting, which hampers
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of Electrical Engineering or related areas. - In addition, the candidate should demonstrate solid knowledge in electric power systems and in the development of optimization algorithms and intelligent systems
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Engineering or related fields. - A solid background in electric power systems is required, as well as experience in the development of optimization algorithms and intelligent systems. - The ability to apply
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modules, reasoning over structured graphs or rules, act as a factual verifier. The PhD fellow will perform the following tasks: Framework Design & Implementation, Reasoning Algorithms Development, and
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models; Participation in the implementation and execution of laboratory tests for validation of the platform's algorithms, interfaces, and subsystems; Support in the analysis of experimental results and in
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validation of artificial intelligence models. Support in the acquisition and management of data collected by the group in a clinical or laboratory setting. Experimental evaluation of algorithms, development