45 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"NIST" PhD positions in Denmark
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. The stipend is open for appointment from January 1st 2027 or soon hereafter. The duration of the position is three years. Your work tasks The project will focus on the development of probabilistic and data
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Are you interested in working with sensitive health data and making a real impact on how it can be used safely and responsibly? At the Center for Clinical Data Science (CLINDA), Department
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of novel methods to decompose the heterogeneity of psychiatric disorders, particularly ADHD, using large-scale genetic, imaging, and epidemiological data from Denmark and other countries. You will apply
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time or other disturbances. If these problems remain unidentified, they can result in incorrect clinical decisions and poor patient management. In this PhD project, you will collect experimental data
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well as carbon and nutrient cycling across a climate gradient. The project will use the terrestrial species data and could include (but not restricted to) automated weather station data, vegetation and
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theory development with comparative measurement, large-scale data collection, observational analysis, surveys, and experiments. It covers Denmark, Estonia, Germany, India, the Netherlands, Switzerland, the
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to analyze and learn from the delivered care and outcomes. Here, AI, particularly NLP, has great potential to extract, structure, and analyze clinically relevant information from these unstructured narratives
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Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position
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experience in Molecular Microbiology, Microbial Genomics/Metagenomics, Culture-based Microbiology, Bioinformatics or Quantitative Data Analysis is an advantage; applicants are not expected to be experts in all
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-scale Microflora Danica dataset combined with samples taken from sites. You will conduct sampling, and apply experimental methods such as metagenomics and metatranscriptomics, linked to soil process data