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with researchers at DTU and KTH, you will help develop an integrated decision-support system that: Uses real-time sensor data and AI models to assess risk scenarios. Dynamically recommends optimal
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sequencing data and optimise editing conditions Execute pooled functional screens to identify synergistic gene combinations Validate hits with targeted assays and in‑vitro models Contribute to B.Sc./M.Sc
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collaboration that covers all aspects of our research: theory and modeling, sample growth and fabrication, experiments and demonstrations. We have created a dynamic research environment of young and senior
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effective enzymatic recycling processes. We are looking for candidates with strong qualifications in some of the following areas, and a motivation to develop within others: Protein chemistry Enzyme kinetics
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bioinformatics, AI and ML software tools to integrate and process the datasets quickly and efficiently. You will also work closely with other computational and experimental biologists to uncover new insights
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mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including
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-polymers using AI-driven process intensification, safe-and-sustainable-by-design principles, and smart polymer formulation. The project brings together leading academic and industrial partners to create a
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. Cox. The position is available starting 1 December 2025. The successful candidates will work on developing new theoretical models and computational methods to investigate the emergence and properties
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monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar ” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU. Application procedure Your
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with a wide range of data formats and engaging with data experts and database managers. The second major focus is advanced data analysis and statistical modeling to identify patterns in fish distribution