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? To address these questions, the PhD candidate will develop and evaluate new decision-support methods that combine optimization and machine learning. Particular attention will be given to methods that can
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master in Computer Science, Bioinformatics or related field Strong programming skills in R Background in machine learning and/or protein structures Fluent in English Specific Requirements Mobility rule
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interest in data analysis, modelling, statistics, and machine learning. Experience in spatial data analysis (GIS), scientific programming (Python, R, or equivalent), or artificial intelligence will be
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well as further professional development. About You You will have a PhD or equivalent in hand at the time of application in Syriac Studies or a related area, and you will have an excellent command of Syriac. You
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simulations using open-source code LAMMPS Publish research results in peer-reviewed journals Present findings at scientific conferences Required Qualifications PhD in plasma physics or a closely related field
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; developing novel ways to combine quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational
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of Informatics at the University of Gdańsk is seeking a a candidate for the position of didactic adjunct. The candidate should a PhD in mathematics or computer sciences and should have: At least seven years of
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
-tier machine learning and computer vision venues, actively participating in departmental seminars, and contributing to collaborative projects. Where to apply Website https://jobs.inria.fr/public/classic
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adaptive resource allocation, AI-driven network orchestration, dynamic beam steering, joint communication and sensing, and cross-layer optimization. Machine learning techniques will be investigated
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; developing novel ways to combine quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational