55 application-programming-android-"Multiple" PhD positions at University of Luxembourg
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, Reasoning and Validation (Serval) research group and work on a research project related to the application of machine learning for official statistics. The subject of the thesis will be “Exploring Large
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Applications should include: Curriculum Vitae with at least 2 references (contact details only) Cover letter Early application is highly encouraged, as the applications will be processed upon
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research the Growing schools; Growing futures initiative, thereby contributing to the research program of the SciTeach Center team, led by Prof. Dr. Christina Siry. The PhD candidate will engage in
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. For more information, please visit our website: www.uni.lu/snt-en/research-groups/finatrax/ Candidates will be enrolled in the PhD program in Computer Science and Computer Engineering with
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adapted from traditional application security testing methodologies and fail to account for the specific challenges posed by GenAI. For example, adversarial attack testing, model inversion vulnerabilities
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Perovskite materials are earth abundant, non-toxic and extremely stable making them ideal candidates for use as absorber layers for tandem and indoor photovoltaic applications. The student will investigate
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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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an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system, with specific focus on cost-effectiveness, emission reduction, and social
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-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system, with specific focus on cost-effectiveness, emission reduction, and