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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
(ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning
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of years are investigated by combining fieldwork, lab work and computer simulations. By bringing together our fundamental understanding of system Earth and our fresh curiosity we conduct research that is
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. Government defensive missions. Our team provides technical guidance in capability and capacity development for Security Operations Centers (SOCs), National Cyber Centers, and Computer Security Incident
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in English (reading, writing, speaking). • Show ability to work independently as well as in a team. • Good knowledge in AI, machine learning, data science and mathematics. • Good knowledge in one
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strong affinity for language data; solid programming skills (e.g., Python) and experience with machine learning or NLP, ideally including transformer-based models and word embeddings; excellent English
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, English or another (if unanimously decided). Internal communication is in German. Therefore a basic knowledge of German or the willingness to acquire such knowledge is essential. Work Location(s) Number
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chemistry. Working with us means learning something new every day. You will be affiliated with the research project, with the working title Q4-BIO, where we open a new field of research around quantum tools
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SD-26109- POSTDOCTORAL RESEARCHER IN AI-BASED ENERGY MANAGEMENT OF RESILIENT MICROGRIDS WITH SECO...
systems and microgrids - Battery energy management systems - Renewable energy integration - Control systems - Artificial intelligence or machine learning for energy applications Experience and skills
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implement a hyperspectral imaging system tailored to bulk forensic trace analysis and develop chemometric and machine-learning models for material identification and classification. You will evaluate
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profiles. Identification of molecular signatures in platelet disorders and bleeding disorders of unknown cause (BDUC). Development of machine learning models for patient stratification. Integration