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research and teaching at the Cybersecurity Engineering Section at DTU Compute, Technical University of Denmark. You could be our new colleague if you are a talented researcher with a passion for research
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Apply Job Description The section for Computational Atomic-scale Materials Design (CAMD) at the Technical University of Denmark (DTU), is seeking an outstanding and highly motivated candidate for a PhD
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with researchers from machine learning and fire safety and material science in a truly interdisciplinary environment. Co-author scientific papers aimed at high-impact journals. Participate in
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anchored at the Department of Civil and Mechanical Engineering at the Technical University of Denmark. The overall project aims to contribute towards the twin Green and Digital Transitions within European
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machine learning, such that you understand the needs in AI research and experimental 3D imaging. The ideal candidate will in addition to strong software development skills, have experience in project
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Excellent communication skills and fluent in English, oral and written Familiarity with analysis of metagenomic data and machine learning techniques is a plus but not essential. Experience with data
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well as pre-clinical data from model organisms. During this project, you will be joining the Single Cell Omics group at the Section for Bioinformatics at the Technical University of Denmark. About the Section
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Skip to main content. Profile Sign Out View More Jobs Postdoc position in advancing chemical impact assessment through machine learning - DTU Sustain Kgs. Lyngby, Denmark Be the First to Apply Job
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with international experts driving technological advancements. Postdoc in Numerical Methods for Magnetism - DTU Energy Kgs. Lyngby, Denmark Posted on 06/04/2024 At the Technical University of Denmark
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organization of large datasets. Experience in machine learning with limited data is preferred. As a formal qualification, you must hold a PhD degree (or equivalent). We offer DTU is a leading technical