19 machine-learning-"https:" "https:" "https:" "https:" "https:" positions at KTH Royal Institute of Technology
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the Job related to staff position within a Research Infrastructure? No Offer Description Two PhD positions in machine learning in our group. One funded by WASP---Wallenberg AI, Autonomous Systems and
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with a strong background in machine learning and LLMs, computer science, and modeling. The candidate will join the project “AI-driven predictive maintenance for buildings: Einar Mattsson (EM) - KTH
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degree in machine learning. The successful candidate will be supervised by professor Aristides Gionis (https://www.kth.se/profile/argioni/ ). The research team focuses on developing novel methods
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from talented and highly motivated candidates to pursue a PhD in machine learning at KTH, Sweden, and NTU, Singapore. This is a fully funded, joint doctoral position that will lead to a joint PhD degree
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support the teaching activities courses at KTH and further develop methodologies and algorithms for the quantum computer simulators. Qualifications Requirements A graduate degree or an advanced level
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risk factors. The main objective is to design and apply machine learning and deep learning methods to understand and investigate the functional behavior of gender-specific cancers. The work will include
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deadline Experience with urban acoustic monitoring or transportation noise assessment Programming skills in Python Knowledge of machine learning techniques applied to acoustic or environmental data
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Computer Science, primarily within the area of machine learning. This is a temporary position at 50% during six months (the percentage and duration may be adjusted depending on starting date). For information about
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manufacturing. It is meritorious to have previous experience in data analysis and processing with Python (or similar), preferably including documented experience with machine learning tools. It is meritorious
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advanced level (higher education) in the research subject or equivalent competence. Experience with deep learning and machine learning tooling.· In-depth knowledge of LLMs and Transformer architectures