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operation Quantum algorithm implementation and benchmarking About you You have a relevant Masters deegree corresponding to at least 240 higher education credits (Physics, Nanotechnology, Engineering, Computer
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intelligence in general. The focus is broadly upon the development of numerically stable and efficient computational algorithms, their implementation and testing with computer programs, both in simulation as
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consequences of higher host specialisation in the tropics – the role of ecological and evolutionary processes, and of data bias), and the successful applicant will work in the Evonets lab (evonetslab.github.io
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includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals that are closely related to applications and applied research
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research funding. There will also be collaborations with industry stakeholders and actors in society. The work will be performed in the Lund Migration Group in the division of Evolutionary Ecology and
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of numerically stable and efficient computational algorithms, their implementation and testing with computer programs, both in simulation as well as real robotic systems. Information about the project and the
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education at the department occurs in an international environment and is focused on animal biology. Our research covers a wide range of topics, from evolutionary ecology and genetics to studies of behavior
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substantially equivalent knowledge in some other way. Candidates must be able to express themselves fluently in spoken and written English. The applicant should have a strong grasp of key concepts in evolutionary
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for doctoral studies, you must hold a Master’s (second-cycle) degree in Genetics, Microbiology, Evolutionary Biology or a related field, or have completed at least 240 credits in higher education, with at least
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computer networking; experience with algorithms for categorisation within large data sets. Some familiarity with concepts and methods from life cycle assessment, and propensity to contribute to simple