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Field
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25th September 2026 Languages English English English The Department of Marine Technology has a vacancy for a PhD Candidate in Deep Learning Enhanced FSI analysis of Modular Floating Structures PhD
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directed evolution of biocatalysts predictable by machine learning. As part of the ML-GUIDE team, you will closely collaborate with researchers to identify commonalities and distinct aspects of engineering
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implementations and hardware-security countermeasures. Experience with hardware reverse engineering, debugging interfaces, or firmware analysis. Experience with machine learning, deep learning, signal processing
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engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 2 Oct 2026 - 23:59 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Is the job
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in computer science, software engineering, human-computer interaction, Medialogy, AI, machine learning, or a related field. The position will require the candidate to work both on the front and back
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technology be designed and evaluated so that it is usable, acceptable and aligned with users’ communication preferences and everyday lives? Your role Your PhD will primarily focus on computer vision and
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) with computational methods. The candidate will obtain single-molecule multiplexing data and validate machine learning predictions using the high-throughput data. The successful candidate will collaborate
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applicants with a background or experience in: • Computational chemistry • Materials simulation • Scientific machine learning / AI • Molecular dynamics or DFT • Materials science or a related discipline
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backgrounds such as AI, computer vision, computer graphics, machine learning, robotics, wearable technologies, textile engineering, fashion technology, digital fashion, or related areas are encouraged to apply
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improved using machine learning techniques. The developed techniques will be applied to metrology of semiconductor samples. Job requirements You are an enthusiastic candidates with a ‘drive’ for applied