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patients Experience with clinical data collection Familiarity with epidemiological methods and registry-based research, epigenetic analyses or machine learning. Interest or experience in science
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registry-based research, epigenetic analyses or machine learning. Interest or experience in science communication and public engagement Experience with publishing biomedical papers Experience with open
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of the position: Follow the faculty’s PhD program Plan design and carry out experiments and their analysis Prepare research articles for peer-reviewed journals (min. 3) Be willing to present results at conferences
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and programming (e.g. R or Python) is required Experience with data analysis related to terrestrial ecology, geography, soil science, or atmospheric sciences. Personal qualities: Strong academic drive
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, Atmospheric Science, Environmental Science, or related fields Good knowledge and skills in statistics and programming (e.g. R or Python) is required Experience with data analysis related to terrestrial ecology
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funding from Petrolia NOCO. About the project/work tasks: The position is affiliated with the project “Reservoir and Seal Characterization & Prediction: An Integrated Workflow Combining Flow-Facies Analysis
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to your work duties after employment. Required selection criteria You must have a relevant Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning
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Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning) or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120
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selection criteria Peer-reviewed publications in relevant fields. Experience with modelling and simulation, e.g. machine learning, parametric design, or finite element tools (Abaqus, Ansys, etc.). Relevant
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“Female Heart”. The researcher position has a temporary financing for two (2) years from 01.11.25. About the project/work tasks: Advanced image analysis of ultrasound images Statistical analysis