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- Technical University of Denmark - DTU
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spring 2026. The position is associated to the ERC Synergy project RECLESS (Recycling versus loss in the marine nitrogen cycle: controls, feedbacks, and the impact of expanding low oxygen regions
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engines. Knowledge of advanced combustion concepts is a merit but not a prerequisite. Practical experience of engine operation in a lab is a merit. Knowledge of control theory is a merit and even better is
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the practical matters of moving to Denmark and working as a PhD at DTU. Application procedure Your complete online application must be submitted no later than 16 January 2026 (23:59 Danish time). Applications
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collaborations are an important part of the operation of the institute. The institute emphasizes a positive and healthy working environment and culture. Living in Iceland offers many appealing qualities. Iceland
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qualifications Responsibilities: Combine enzyme and process engineering supported by machine learning as described above Participate in training events, workshops and secondments within MSCA doctoral network
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. Our activities span enzyme and microbial systems, process intensification, and control strategies, with the aim of linking fundamental insights into biocatalyst behavior to robust process implementation
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analogous neural circuitry and shared molecular pathways have established songbirds as the model system of choice for human speech learning and fine motor control in general. The PhD candidate will use
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quantification of intermediates, products and byproducts will further be developed, as well as reaction tracking. A second PhD student on the project will be responsible for developing the catalytic process and
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industry. Responsibilities and qualifications Your overall focus will be to advance the development of a sustainable photochemical reduction process for PFAS mineralization using a green reducing agent. You
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languages and platforms (e.g., C/C++, Python, real-time operating systems). Research experience in artificial intelligence, real-time control systems, or adaptive system architectures. Familiarity with