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of Zurich) and Dr. Michael Siegenthaler (KOF). Using large-scale linked register and survey data and self-collected data on collective bargaining agreements in Switzerland, the primary research goals
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. The team uses innovative large datasets and applies rigorous empirical methods to estimate causal effects. The successful candidate(s) will be part of the PhD programme of the Department of Management
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physiological sensors, and manage the data streams and data archive that originate from these sensors. The second task is to perform original research at the experimental site in physiological plant ecology
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industrial needs, we are looking for a postdoc holding a PhD in material science, physics or chemistry, with a clear link to X-ray based analytical methods, preferably related to X-ray diffraction. The project
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Postdoc position on ultra-long read sequencing for animal epigenomics, transcriptomics, and genomics
to address with (ultra) long read sequencing A Curriculum vitae including a list of publications, complete academic record, and copies of Bachelor's, Master's and PhD degrees Names and contact information
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Institute for Research in Biomedicine, Università della Svizzera italiana | Switzerland, | Switzerland | 29 days ago
) to the study of immune response. The position offers a unique opportunity to engage in cutting-edge research applying large language models (LLMs) for antibody discovery. Funding and Duration The project is
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qualitative and quantitative data in a structured manner. The work will range from qualitative case studies to large-scale quantitative studies. Design interview guides based on the study purpose and latest
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are required Experience with handling radioactive materials is a big plus Good knowledge of English, knowledge of German is an advantage First experience in project management Additional Information Benefits We
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: Collection of large scale administrative and survey data Managing, cleaning, and creating raw data sets Managing and coordinating two large-scale projects with a large research team and various policy
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in the field of production engineering. A further research focus is on novel topics such as additive manufacturing, Artificial Intelligence (AI), Machine Learning (ML), Big Data Analysis or Industry