206 data-"https:"-"https:"-"https:"-"https:"-"University-of-Minho" positions at ETH Zurich
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recommendation A brief research plan (1 page) Applications sent via e-mail or postal services will not be considered. For further information, please visit our group website consult our published work
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brief research plan (1 page) Applications sent via e-mail or post will not be considered. For further information visit our group website , consult our published work , or contact Professor Martin
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environments (Schmidt, Science, 2022) — especially in the context of drug–host microbiome interactions — and developing dedicated tools and analytic workflows for the novel data modalities generated by Record
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portal. The deadline for applications is the 3rd of May, 2026, with a start date of Summer-Autumn 2026. Further information about our groups can be found on the Planetology and High Pressure Group
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. ENDOTRAIN will train a new generation of interdisciplinary experts who merge clinical endocrinology, artificial intelligence, data science, engineering, ethics and law into an integrated field of digital
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), highly resolved (hourly‑scale) data on species presence, abundance, and movement patterns in rivers and streams. To address this gap, this project aims to realise the Riverine Organism Drift Imager (RODI
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collection. This position aims to synthesise all available information from these natural fungal isolates to build hypotheses for which genetic features are essential for horizontal transfer. Job description
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and coordination experience Further information about NCCR CLIM+ can be found on our website . Questions regarding the position should be directed to Prof. Sonia I. Seneviratne, sonia.seneviratne
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for this position and group. Research Proposal (1-2 pages) outlining a potential research project you would like to undertake. Contact Information for two academic referees Further information about
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frames). Project background The work focuses on data-driven generation of structural systems. You will be involved in developing, experimenting with, and evaluating machine learning models that help