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and reduction of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts
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You have academic qualifications at PhD level, for example within the areas of bioinformatics, machine learning or forensic odontology. We favour experience in computational data analysis, and the
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will be using metabarcoding for the analysis of microbiomes from field and greenhouse experiments, and you will integrate data on microbiome composition, nematode infestation, plant performance, plant
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successful candidate will have previous experience in computer science or data science, with a PhD and publications in at least one of the following areas: Formal modelling and verification of business
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international quality, including publication. Single cell RNA sequencing and data analysis Characterization and production of monoclonal antibodies Flow cytometry Confocal microscopy qPCR In vitro cell cultures
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. Qualifications Applicants with experience in mixed methods, particularly digital methods, data scraping/analysis and qualitative research (Netnography and interviews) will be preferred. Proficiency in English and
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. The overall goal of the project is to design a novel high temperature heat pump. You will be conducting Computational Fluid Dynamic (CFD) simulations and cycle analysis, which will be instrumental
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and technicians to solve analytical challenges and develop, optimize, validate and apply analytical methods to evaluate food safety. Key Responsibilities - Perform trace-level analysis of organic
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. The overall goal of the project is to design a novel high temperature heat pump. You will be conducting Computational Fluid Dynamic (CFD) simulations and cycle analysis, which will be instrumental
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quantitative data collection and analysis. We’re looking for a colleague who is passionate about the research topic, highly organized and able to work independently, and able to work collaboratively in