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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
the potential of biological systems. Big data approaches and analysis of biological systems are key research instruments at the Center. DTU Biosustain utilizes these advances for microbial cell factory design to
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contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models, alongside complex drug screening, efficacy
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psychology A successfully completed scientific university degree in psychology Accurate working and strong team spirit Confident handling of large, longitudinal data sets Competent use of statistics and data
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group specializes in experimental quantum technologies spanning quantum information processing, quantum communication, and precision sensing. In this PhD project, you will work at the forefront of solid
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recent large-scale capabilities in physics. Reliability, exploring uncertainty quantification and robust inference in machine learning. Explainability, leveraging identifiability and unique recovery
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protocols for electrical biasing of samples in the microscope. A key task is to process and analyse large 4D-STEM data sets and extract information about domain wall structure and dynamics. The role involves
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Human Behaviour in projects targeting social good. Research at N/LAB focuses on the development and application of innovative computational methods using Big Data, Behavioural Science and Machine Learning
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the effectiveness of anticipatory cash transfers in response to climate disasters, using large-scale RCTs in Bangladesh and other countries. It investigates how early interventions can mitigate the impacts of extreme
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the research group (e.g., organising our weekly meetings, contributing to our social media accounts, administering internal group information) This is part of your existing profile: Completion
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase