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and unsupervised machine learning models, including LLM-based classification and fine-tuning for domain-specific applications. Collaborate with faculty and research staff on data collection and analysis
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
Position overview We are seeking applicants for an 18-months postdoctoral fellowship focusing on the development of an AI-based phenotyping system for high-throughput screening for aphid
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environmental quality. The fellow will contribute to field and laboratory studies, data analysis and modeling, publication of results, and development of decision-support tools for producers, advisors, and agency
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libraries (spaCy, NLTK, Hugging Face). Machine learning fundamentals and model evaluation. API integration and version control (Git). Prototyping, testing, and refining NLP-driven applications. Applying human
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management, knowledge bases, ticketing systems, and communication platforms. Deploy models to production environments following established MLOPs practices and ensuring appropriate monitoring. Performance
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laboratory experience in areas relevant to the project, namely: needs diagnosis and assessment; development of artificial intelligence-based forecasting models; and development of optimal control models
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Job Description As Senior Researcher, you will join our Section for Ecosystem Based Marine Management in Lyngby, where 35 employees work to advance interdisciplinary research and improve our
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are in compliance with CSU and Campus requirements Provides financial research and financial analysis/modeling in a variety of matters including but not limited to the procurement of capital equipment and
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successful candidate will be expected to develop a dynamic, externally funded research program that addresses key challenges in the areas of Dynamics Systems and Control. Successful candidates will contribute
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the scope of the R&D project of Center for Microelectromechanical Systems (CMEMS-UMinho), “Smart Control of a Soft Exoskeleton with a Textile-based Actuation”, COMPETE2030-FEDER-00761900, co-financed by