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particular, in the areas of continuum mechanics of solids, computational mechanics and machine learning Willingness to independently familiarize oneself with new subject areas and work on interdisciplinary
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | about 2 months ago
Tyrol with state-of-the-art shotgun metagenomics, microbiome and resistome analyses, ecological network modelling, machine learning, and synthetic microbial community (SynCom) experiments. The PhD
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lit. b (postdoc) Limited contract until: Job ID: 6036 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if
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data-driven modeling. The successful candidate will develop and apply data-driven methods for chemical discovery and molecular design. These methods include machine-learned interatomic potentials, data
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the development, evaluation, and practical application of machine learning methods (especially deep learning) Publication of scientific results in renowned international journals and conferences Supervision
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contributions to improve the quality of obstetric care. Ideally, modern and future-oriented aspects will be considered, including digitization, smart sensors, Artificial Intelligence (AI), and machine learning in
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for chemical discovery and molecular design. These methods include machine-learned interatomic potentials, data-efficient and uncertainty-aware modeling, enhanced sampling, and statistical thermodynamics
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multidisciplinary team of experienced researchers, closely collaborating with another PhD candidate who will focus on the data science, models and machine-learning aspects of the project. PhD researcher position in
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intelligence, or related areas Experience with large language models, machine learning systems, software testing, program analysis, requirements analysis, or software quality assurance Strong programming skills
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Research Center for Molecular Medicine (CeMM), ÖAW | Graz 12 Bez Andritz, Steiermark | Austria | 2 months ago
; and how these mechanisms can be understood, modelled and ultimately perturbed for biomedical discovery. Two scientific tracks Track 1: Computational Biology / Machine Learning for membrane protein