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probabilistic frameworks. Experience with machine learning or AI methods for localization or perception (e.g. learning-based SLAM, data-driven sensor fusion) is a plus. Underwater or field robotics experience
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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated
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data in any area of finance, such as asset pricing, machine learning, ESG investing, how social networks affect finance, research replicability, regulatory data in finance, financial institutions, and
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catalysts for the synthesis of a range of industrially valuable compounds. This PhD project is part of the Horizon Europe Marie Sklodowska-Curie Action (MSCA) doctoral network (DN) ELEGANCE (machinE LEarning
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) ELEGANCE (machinE LEarning for inteGrated multi-parAmetric eNzyme and bioproCess dEsign), and it will focus on: Expression, characterization and application of enzymes from University of Turin and other
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF
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polar orbit, passing near the poles about 15 times per day and regularly observing the CIFAR study region. Its payload - two optical cameras, a thermal camera, and onboard machine-learning capabilities
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twins, energy islands, electrolyzers, and machine learning. Our team of 26 members from 13 different nationalities values diversity and includes experts in a broad range of scientific disciplines
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mechanics, vibrations, and their active control, as well as machine elements and design optimization. The section has a scientific staff of about 25 people and 20 PhD students. The research rests
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, Denmark [map ] Subject Areas: Nonparametric estimation, Machine learning methods in econometrics and time series analysis, Statistics for high-dimensional data, Stochastic volatility models Appl Deadline