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development, supervision, and external funding initiatives. What we expect Applicants must hold a PhD in Energy Informatics or in a closely related field such as Artificial Intelligence, Data Science, Computer
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learning Distributed and federated training The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another
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researcher network. The department consists of nine research sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe
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data. We also offer a great mentoring experience, a collaborative environment in which the candidate will be able to share across subfields and applications, and a research environment characterized by
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decarbonization challenges at regional, national, and international levels. For more information about SDU LCE, please visit www.sdu.dk/lifecycle. Profile and Responsibilities We are seeking a highly motivated
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: Establish and develop experimental protocols and pipelines and implement data management compliance. Presentation of your work in various meetings (locally at the department, national and international
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. The position also involves applying computational tools to guide enzyme selection and cascade design, as well as to interpret kinetic and screening data. The candidate will document methods and results in a
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diagnostic pathways. Core research tasks include planning, conducting and publishing epidemiological studies using large-scale observational data, primarily register-based, with a focus on effects of ADHD
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across news outlets, social media platforms, and individual news diets, drawing on, among other data sources, data donations from individuals and automated content analyses. SP2 will examine how people
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on “ Integrating AI into Aquatic Ecosystem Models to Decode Ecological Complexity ” funded by Villum Fonden. Within that project, the focus is on exploring novel ways to infer information from environmental data