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learning, optimization, mathematical foundations of artificial intelligence, mathematical ecology and mathematical statistics. Qualifications To qualify as a postdoctoral scholarship holder, the postdoctoral
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core mechanics (game design) Model the BDI (Beliefs, Desires, Intentions) agent system to be learned by the AI Program the game application specifically for mobile devices Evaluate the game's
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data and deep learning methods to assess canopy cover, quality, carbon stocks, and ecosystem services. Mandatory requirements: PhD in areas related to forest resources, remote sensing, data science, or
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angle scattering Ability to communicate (written, spoken) in English Awareness of diversity and equal opportunity issues (specific focus on gender equality) Great emphasis will be placed on personal
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as a member of the GHER contributing to the EU research project COMEDI in a consortium of 11 leading partners in the field of data assimilation and deep learning. A successful applicant will develop
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learned from ESA research and development activities relating to Zero Debris and consultation with ESA domain experts to identify challenges, constraints and opportunities associated with developing space
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pipeline according to project requirements A good communication skills with a good command of written and spoken English and Chinese Able to work independently and in a multidisciplinary team Experience in
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project TARGETWISE. The candidate will be responsible for conducting machine learning omics data analysis within the computational team. The details on responsibilities, obligations and rights
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the division of Data Science and AI , we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and
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, preferably in food chemistry; knowledge of e-learning methods is desirable. Mentorship: Experience in supervising doctoral and Master's students. Language Skills: Excellent English skills (C1 level