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Field
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for Biosustainability (DTU Biosustain) Recent progress in our ability to read and write genomic code, combined with advances in automation, analytics and data science, has fundamentally changed the scope and ambition
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data collection approaches. Familiarity with or strong motivation to learn machine learning or advanced data analytics for pattern detection and forecasting in environmental data. Familiarity with
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related subject. A PhD (or be close to submission) in Physics, Mathematics or a related subject. Experience Experience in conducting high quality academic research. Strong publication record in peer
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quantitative analytic methods. Core responsibilities include: Conducting data analysis for ongoing projects. Developing independent and collaborative publications by accessing available longitudinal data
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But Degree (ABD) status will also be considered for interviewing. Strong applied quantitative data analytic skills and experience conducting statistical analyses with large databases. Strong writing and
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. This is part of your personality: Completed doctoral/PhD studies in subject chemistry, preferably in analytical chemistry or equivalent qualification, PhD in chemistry or biomedical research Profound
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will involve a combination of simulation and statistical modelling. Your key responsibilities will be: Lead analysis of State response data to estimate detection, occupancy, and spread of PSHB Engage
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of PhD), or Research Associate (more than 3 years of PhD). A strong preference is for individuals with (a) computer science or computer engineering degrees with previous experience in natural
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of information processing), and formal epistemology (in particular, formal representations of inattentiveness and unawareness). This project will involve philosophical / linguistic analysis, experiments with human
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in both oral and written English is essential. Research experience with single-molecule methods, FRET, cryoEM, microfabrication, and/or data analytics is strongly preferred but not mandatory. Job