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modelling methods to design resistance-proof antibiotics. You will join an interdisciplinary team, integrating machine learning, medicinal chemistry and microbiology. You will work with Asst. Prof. Eli N
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and methods added to his/her toolbox. The project deals with biotechnology, nanotechnology, physics, material sciences, and physical chemistry, so a broad range of candidates will find new knowledge
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and/or professional training in digital health and health innovation; b) Experience in applying mixed methodologies, including quantitative and qualitative methods; c) Knowledge of digital health
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, cultivating interdisciplinary dialogue, and an interest in teaching and mentoring undergraduate students. The anticipated teaching load will be one formalized course per year, AS1111 Milstein First-Year
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related to staff position within a Research Infrastructure? No Offer Description The Neuro-Symbolic AI Group at the IDIAP Research Institute operates at the interface between neural and symbolic AI methods
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on understanding how different excitation methods generate polarons and correlated materials in the cuprates and other quantum materials, building on our recent results in the vanadium dioxide (see Johnson et al
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problems. Ability to exercise sound judgment in making critical decisions. Bilingual (English/Spanish) – very strongly preferred Have received formal training in implementation science (e.g., graduate level
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programming (C++, MPI, CUDA/HIP/ROCm). Preferred Qualifications: Familiarity with LLVM/MLIR development and multi‑language IR ecosystems. Background in formal methods or automated reasoning. Experience with
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the phenomenology of cognition (e.g. formalizing concepts such as reasoning, agency, meaning, or experience into testable computational models, skill acquisition, and affordances). The successful candidate will bring
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refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role Develop innovative methods and data-driven AI tools for highly dynamic SatCom systems Implement and open-source proof-of-concept