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projects, including the flagship EXCELSIOR H2020 Teaming Project (https://excelsior2020.eu/ ), as well as DIGIFARM, NOSTRADAMUS, CERBERUS, and CARBONICA. ERATOSTHENES Centre of Excellence is an autonomous
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biological or other research data. Utilizes and develops algorithms, computational techniques, and statistical methodologies. Helps in the design of new experiments. Implements end-user needs in database
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machine learning methodologies, develop algorithms for health monitoring and patient clinical outcome prediction, and address ethical considerations. The role also requires attending weekly meetings, report
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, interviews and/or focus groups; Solid knowledge in the field of health; Experience in the development of interactive digital tools or educational platforms (valued but not mandatory); Fluency in English
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reactivity across diverse materials, such as catalysts, quantum materials, energy storage systems, and superconductors, you will develop and deploy cutting-edge AI/ML algorithms for real-time Extended X-ray
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the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations
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Doctoral student in development of nanowire devices for photonic neuromorphic computing (PA2026/472)
and analytically, to solve problems independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your
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environment to support agricultural decision making with advanced remote sensing and geospatial technologies. Responsibilities: Develops advanced Agro-geoinformatic algorithms for monitoring and predicting
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Projection Chambers used in the Deep Underground Neutrino Experiment. This work involves parsing the simulated data to extract and analyze the information necessary to develop an algorithm to determine the
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development of post-graduate students. Particular attention will be given to candidates with experience in topics that are relevant to data science, most notably mathematical and algorithmic foundation