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contact details of 3 referees Applications should be submitted in English. Enrollment at the University of Basel for the successful candidates is mandatory. For more information, please contact Professor De
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situation into account and asks for relevant information. People with disabilities will be given preferential consideration if they are equally qualified. The University of Tübingen strives to increase
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statistics. You will also collect data independently, conduct surveys and organise workshops with companies, policymakers and academics, under the supervision of two academic promoters. In addition, you will
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measurements in particle physics. Many of my projects are informed directly by current measurements, e.g. addressing new or unexpected features seen in the data. Others focus on improving the formal accuracy
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10 Feb 2026 Job Information Organisation/Company Institute of Inorganic Chemistry of the Czech Academy of Sciences Research Field Chemistry » Inorganic chemistry Chemistry » Inorganic chemistry
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field. Expertise in analysis of single cell or spatial sequencing data is required. Experience in analysis of bulk RNA and whole exome sequencing data, and genotyping array data is preferred but not
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with existing population and demographic monitoring data held by the British Trust for Ornithology. Statistical modelling approaches will examine spatiotemporal changes in bird distributions in response
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Max Planck Institute of Immunobiology and Epigenetics • | Freiburg im Breisgau, Baden W rttemberg | Germany | about 24 hours ago
deadline More information about the programme and on how to apply can be found on our website . Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree
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treatment. ENDOTRAIN will train a new generation of interdisciplinary experts who merge clinical endocrinology, AI, data science, engineering, ethics and law into an integrated field of digital endocrinology
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they can reliably, affordably, and fairly support a net-zero energy system. The research will focus on how data-driven and machine-learning-based control can coordinate demand, storage, and local generation