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Post-doctoral fellowship (PDF) description: This post-doctoral fellowship (PDF) will harness the large amount of data generated from this site using various remote sensing systems as well as ground
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Job description: At the University of Vienna more than 10,000 personalities work together towards answering the big questions of the future. Around 7,500 of them do research and teaching, around
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time. Collaborate on project and analysis design guided by their PI. Develop new computational methods. Adhere to field and lab standards for data analysis. Identify, process, organize, interpret, review
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analyzing data from large cohorts, ideally within the NAKO German National Cohort Experience in teaching epidemiology to students Desirable qualifications Experience in the field of metabolic diseases
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, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific literature). Our
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data mining. The group provides a strong network to local AI expertise (e. g. Hessian.AI, TU Darmstadt), large scale compute infrastructure, as well as a broad international network (Stanford, UC San
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SAXS and Large scale facilities SAXS (from proposal writing to execution of experiments and data analysis for the latter) Experience with protein purification Advanced knowledge in research design and
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given to applicants who have received their Ph.D. degrees in behavioral neuroscience or related fields within the last 3 years and have experience in computational neuroscience and data mining using
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the integration of large-scale biological datasets derived from both the host and the microbiome, employing advanced statistical methods and cutting-edge artificial intelligence techniques to uncover novel insights
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collaborative research on immune development and responses to respiratory viruses. Analyze clinical and large-scale datasets (e.g., genomic, transcriptomic, proteomic data). Design and execute experiments using