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, Computer Science and Artificial Intelligence. The position is embedded in the Multi-Agent Systems group of the department of Artificial Intelligence of the Bernoulli Institute. Qualifications PhD in Computer Science
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international and most innovative employers in the region. With more than 6000 employees from 100 different countries, we are helping to build tomorrow's world every day. Through top scientific research, we push
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collaboration with an interdisciplinary team including biologists, pedologists and other experts. You will work with various types of spatial data collected from multiple sources and at different scales. We
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academic staff and postdoctoral researchers from over 20 different countries. Our research aligns with the needs and challenges of industry and society. We achieve this by advancing knowledge in: advanced
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the contribution of different proteins to parasite transmission. You will uncover new biology for the important parasite. You will have the opportunity to engage in meaningful collaborations
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factors in Bacteroides. Projects include identifying the genes regulated by each of the 32 different HTCS transcription factors in B. thetaiotaomicron; identifying regulatory networks for preferential
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processes for data standardization, data warehousing, quality assurance development and data analysis. A successful candidate will work closely in different aspects of the quality assurance and data
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plasticity metrics derived from functional MRI data. Investigate developmental differences in infant brain functional networks Support generation and testing of improvements for code bases for the analysis
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(PISCES) with different climate change scenarios and biogeochemical model complexities over centennial and millennial timescales. This will allow you to identify the key drivers of biological carbon storage
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. Qualifications PhD in Computer Science, Economics, Mathematics, or a closely related dis-cipline. Strong background in computational social choice, algorithmic game theory, or AI safety. Excellent research track