19 programming-language-"University-of-Ferrara" PhD positions at University of Luxembourg
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proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C++). Prior proven experience in data-driven innovation projects is
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Skills: Strong programming skills are an asset Soft Skills: Most importantly, we seek individuals who are curiosity-driven especially interested in interdisciplinary research, eager to continuously learn
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professors Copies of diplomas, transcripts with grades (English translation is required) Proof of English language proficiency (if available) The motivation letter should identify up to two EICCA research
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We are seeking a highly motivated PhD candidate with a strong interest or background in AI as well as in one or more of the following areas: Generative AI, Natural Language Processing, Deep learning
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). This project aims to accelerate the energy transition in Luxembourg by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system
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Pathogenesis in the age of the microbiome (MICRO-PATH; https://micro-path.uni.lu ) is a highly competitive, interdisciplinary, research-intensive PhD training programme, supported by the PRIDE
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Applications should include: Cover letter explaining your motivation for applying and any relevant research and language skills and prior experience Curriculum Vitae Degree certificates and
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Applications, written in English, should include: Cover letter explaining your motivation Curriculum Vitae (including your contact address, work experience) Copies of diplomas List of publications
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The PhD candidate will generate and study complex macroscopic flow patterns of LCE precursors, polymerize the precursors into LCEs programmed by the flow patterns, and study the resulting actuation
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). This project aims to accelerate the energy transition in Luxembourg by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system