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to structured spectral annotation supporting advanced downstream data analysis (in collaboration with a dedicated postdoc) Present research findings through peer-reviewed publications and international
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impact of energy costs” The project aims to achieve breakthroughs by: Developing stochastic control problems for wealth optimisation, with a focus on the balance between consumption and savings. Analysing
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focuses on developing and applying digital technologies such as additive manufacturing/3D printing, numerical modelling, artificial intelligence, automation and robotics, digital twins, and smart materials
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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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analysis. Basic as well as applied research are conducted on some of the major challenges facing society, such as pollution and pollution control mechanisms, management of land, soil, water, air and
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. The successful candidate will be based in Odense, under the primary supervision of Prof. Ricardo J. G. B. Campello , but they will be expected to also work closely with other PhD students, postdocs, and
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PhD project in collaboration with supervisors Design and develop management and real-time operation tools for ePIPV Test controlling functionality in a state-of-the art real-time experimental facility
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of the genotypes. The PhD student will work together with a postdoc on the project. Description of the scientific environment The PhD student will be hosted in the Crop Physiology and Production Systems research
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bioinformatics including NGS (Nanopore, Illumina, PacBio) Experience with automation and coding in Python or other programing languages Experience with protein software tools like AlphaFold3, Boltz2, PyMOL
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tasks will be: Plan and manage your PhD project in collaboration with supervisors Design and develop management and real-time operation tools for ePIPV Test controlling functionality in a state-of-the art