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). The project envisions the use of methods such as: Large Language Models (LLMs) to hold a knowledge base of regulatory documents Reinforcement Learning (RL) for adaptive decision-making under uncertainty Dynamic
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is part of DTU’s Tenure Track program. Read more about the program and the recruitment process here . You can read more about career paths at DTU here . Further information Further information may be
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part of DTU’s Tenure Track program. Read more about the program and the recruitment process here . You can read more about career paths at DTU here . Further information Further information may be
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using real operational data from a large wind turbine portfolio. Project Responsibilities and Qualifications As a Doctoral Candidate in the MET2ADAPT network, your primary research tasks will focus
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. metabolic rate (respirometry) and thermal preference and avoidance Investigating growth rate and thermal experience from analysis of otoliths Analysing data using R or similar statistical software. Writing
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-connected working environment. Close collaboration with NADARA will allow you to apply and validate your methods using real operational data from a large wind turbine portfolio. Project Responsibilities and
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excited about large challenges and enjoy solving them, have an extraordinary drive towards achieving groundbreaking results, and love physics discussions as well as participating in thoughtful conversations
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of harnessing 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
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to include: Designing and conducting fish experiments in aquaculture facilities Collecting biological samples and observational data Participate in degassing trials Perform a variety of biological and water
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cardiometabolic diseases by integrating registry data, large-scale GWAS and other omics datasets, as well as data from human clinical trials. A subproject will be based on biobanked and newly collected human saliva