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Applications should include: Curriculum Vitae Cover letter Contact information of two or three referees Research statement and topics of particular interest to the candidate (max 1 page) Early application is highly encouraged, as the applications will be processed upon reception. To ensure full...
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Application Deadline 17 Feb 2026 - 01:11 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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website: https://wwwen.uni.lu/snt/research/finatrax/projects. The Ph.D. candidate will focus on information systems within computer science and engineering while collaborating with Luxembourg’s Ministry for
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will pursue a Ph.D. degree (Doctorate) in computer science or software engineering with a focus on differential privacy (DP) and other secure computing techniques while collaborating with the Ministry
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Applications should include: Curriculum Vitae Cover letter A one-page research proposal (referencing the HOFA3 chapter) Transcript of academic records (including grades) and copies of diplomas Names and contact details of at least two references willing to write recommendation letters (they will...
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, Large Language Models, Human-Computer Interaction, Virtual reality. The selected candidate will work on the design and implementation of a human-computer interface to support education using an AI-based
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diverse backgrounds (e.g., economics, engineering, computer science, information systems, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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Qualification: Master in Computer Science and/or Cybersecurity or equivalent degrees with expertise in at least one of the above areas (dependability, real-time systems, operating systems
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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
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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