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. Candidate profile: The ideal PhD candidate should have strong knowledge of quantum mechanics and mathematics, should have strong skills in analytical derivations and be willing to acquire computational skills
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in immunology. practical experience in immunology, flow cytometry and microscopy; strong analytical and problem-solving skills; a flexible, pro-active team spirit; excellent communication skills in
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mitigation strategies. The results will support the development of evidence-based conservation protocols and can provide a learning dataset for AI informed decision that is still lacking in the domain. What we
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-good university degree in economics - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) - a high motivation and the
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, environmental economics, agricultural sciences with a focus in economics, or related disciplines - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics
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machine learning e.g., GNNs, graph representation learning, hierarchical or probabilistic graph models Strong analytical and problem‑solving abilities, with enthusiasm for developing novel computational
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specialization. Requirements We are looking for candidates who have: Solid analytical and mathematical abilities Experience with machine learning Experience with formal language theory or automata theory Strong
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and migrations of ancient humans in Eurasia; Other ongoing projects in the Laboratory of archaeogenetics, such as testing and improvement of analytical methods such as PCA and manifold learning
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analytics, geographical information science, satellite positioning, ubiquitous positioning, photogrammetry and remote sensing, geodesy and geodynamics, environmental monitoring, geo-hazards studies
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and a strong interest in organic synthesis, carbohydrate chemistry, and/or chemical biology Demonstrate analytical skills in the laboratory Be curious, motivated, and enthusiastic about