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to: Collect data through e.g. literature studies regarding the raw materials to be used Perform data analysis and interpret results from chemical and microbial analysis of the raw materials Carry out product
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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 are supported by
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Postdoctoral research fellow in taste receptor pharmacology at the Department of Biomedical Sciences
. Experience in several of the following topics is an advantage: Pharmacological assays (e.g., cell-based, ex vivo, or in vitro) and quantitative data analysis using GraphPad Prism, Python, or Jupyter Notebooks
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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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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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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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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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heterostructure quantum devices Perform electrical measurements (i.e. magnetotransport) at room and/or cryogenic temperatures Participate in TEM and nano-ARPES characterisation and analysis Collaborate with project
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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
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interventions providing guidance and motivation. Building on an extensive behavioral analysis of bystander behavior in response to online hostility conducted within the ERC-CoG STANDBY-project, we have developed