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economics, market design, and policy-relevant research. Experience with numerical, computational, or simulation-based methods (e.g. Matlab, Python, R, or similar); experience with statistical software is an
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or geospatial data and Explainable AI or causal inference; strong programming skills (Python required); the ability to work in an interdisciplinary medical–AI–public-health team; Good command of English
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refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas. This PhD project aims to develop
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data and Explainable AI or causal inference; strong programming skills (Python required); the ability to work in an interdisciplinary medical–AI–public-health team; Good command of English; Experience
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part of the project, and hence skills in computations and implementation (via codes written in open source software, such as R, Python, ...) are a plus. A good knowledge of written and spoken English is
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come from one of the following countries: https://www.ugent.be/nl/onderzoek/financiering/bof/dos/countrylist.pdf More information about the scholarship: https://www.ugent.be/en/research/funding/bof/dos
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analysis software (e.g., Fiji/ImageJ). Advanced Cell Manipulation (e.g., genome editing via CRISPR/Cas9, flow cytometry/FACS). Basic familiarity with data analysis tools (e.g., GraphPad Prism, R, or Python
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of the hallucination detection system under diverse visual and textual conditions Primary experiments will be conducted in CARLA (https://carla.org), enabling controlled and repeatable evaluation of hallucinations under
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, critically-thinking, self-motivated, flexible, and enjoys working in a team Desirable but not required: Programming experience, preferably in Python or R, and experience in the Linux environment Experience
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Python or R, and experience in the Linux environment Experience with large-scale data analysis, such as genomics or transcriptomics data Experience with a workflow management system such as Snakemake