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interpret multi-modal data (e.g., omics, images, etc.). The ideal candidate has the following skills PhD or MSc in computational biology, statistics, mathematics, computer science or related topics Advanced
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analysis Experience with next and third generation sequencing data quality control Experience with data management, visualization, and interpretation, including proficiency in statistical analysis Experience
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management, visualization, and interpretation, including proficiency in statistical analysis What we offer in return DTU is a leading technical university globally recognized for the excellence of its research
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, Mathematics, and Statistics. The position is a full-time position. The expected start date is during the fall of 2024, but we are flexible on the start date. Responsibilities and qualifications We are looking
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Skip to main content. Profile Sign Out View More Jobs Part-time Assistant in Management Science – DTU Management Kgs. Lyngby, Denmark Be the First to Apply Job Description We are looking for a part-time assistant with a background in programming and decision science to support research...
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large datasets acquired under challenging conditions. This allows us to gain statistically relevant data and map out the influence of external parameters while working under relevant conditions. In situ
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Preferable knowledge of statistical and machine learning methods You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree
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include: Create a digitalized platform for sustainable lifestyles, bringing together the individualized household data from Danish statistics on household consumption and spending, including energy
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PhD fellowship in conservation science - developing and validating indicators of ecosystem integrity
experience in field, database and GIS work on biodiversity and ecosystem processes, such as ecohydrology, nutrient dynamics and carbon pools, as well as statistical modelling will be considered assets.Fluency
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with a range of multi-omics data types and associated bioinformatic algorithms/statistics. Familiarity with methods for computational modeling of metabolism (constraint-based, kinetic modeling, etc