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Field
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working with heterogeneous datasets originating from different sensors or data sources. Familiarity with forest ecology, biodiversity, or natural-resource applications. Experience developing reproducible
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 1 month ago
the application of various ML algorithms, including supervised algorithms for environmental predictions, as well as unsupervised algorithms for clustering and LLMs/Transformers Experience with sequence data
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through a mixture of qualitative, quantitative, and sensor based approaches to assess student experiences. Rather than seeking to “fix” individual students, our project challenges stigma by addressing
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with European industry. The EISLAB division at Luleå University of Technology conducts research in electronic systems design, sensor systems, cyber-physical systems, the Internet of Things and machine learning
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Current reseach is in the areas of: Development of biomimetic structures as ultrasound contrast agents Deep tissue imaging using photoacoustic contrast agents All optical photoacoustic sensors
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. The EISLAB division at Luleå University of Technology conducts research in electronic systems design, sensor systems, cyber-physical systems, the Internet of Things and machine learning, and works on
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. Thus a background in fluid mechanics (marine hydrodynamics or aerodynamics) is required. Knowledge of measurement technology and relevant sensors, as well as industry experience from the industry
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: Wireless Communications Group: Mobile Systems - Av Work Objectives: Energy-efficient wireless power transfer system using RIS-enabled beamforming and optimized power management algorithms to ensure
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- Geometry, Learning, Information and Algorithms - Speech and Cognition The Gipsa-lab comprises 150 permanent staff and approximately 250 non-permanent staff (doctoral students, post-doctoral researchers
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algorithms. Vision Language Model (VLM) experience is desirable. Qualifications A high-grade undergraduate degree (first class or upper second) in computer science or MSc in related field. Skills Knowledge