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transport planning and software engineering for policy makers and communities. As a PhD fellow, you will: Lead the development of advanced spatial analytics tools and toolkits combining GIS, Python, R, GeoAI
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proficiency, particularly in Python Experience with or strong interest in, Language models (SLMs/LLMs), Agentic AI systems, Deep learning architectures, Multimodal AI (e.g., text, time-series, sensor data
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, and diagnostics relevant to helioseismic inference. Development and maintenance of robust, reproducible analysis workflows (Python and/or Julia-based; HPC-oriented handling of large datasets). Depending
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degree (master level), it must be equiva-lent to a master in the Norwegian educational system Documented proficiency in scientific programming (e.g., Python) Documented proficiency in deep learning
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tools used in AI or interactive system development (e.g., Python, Max/MSP, Unity, Unreal, etc) is an advantage. Applicants should possess understanding of user-centred or participatory design methods and
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participate in the research environment at GAMUT. Fluency in programming and digital tools used in AI or interactive system development (e.g., Python, Max/MSP, Unity, Unreal, etc) is an advantage. Applicants
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(e.g., carbon, nutrients, oxygen) or transient tracers such as CFC-12 and SF6, is required. Proficiency in MATLAB or Python is required. Applicants must be able to take part in a nearly two-month-long
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characterization is a plus Experience with biomedical applications is positively evaluated Experience with data analysis using, e.g., Origin or MatLab Programming skills, e.g. proficient with Labview or Python
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for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defense are eligible for appointment. Programming skills in GAMS and Python. Experience with HPC. Experience with
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have until 30.06.2026 to complete the final exam. Desired / Beneficial qualifications: Valid driver’s license. Programming and numerical analysis skills (e.g., Python, MATLAB) and/or experience with