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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 2 months ago
analysis, machine learning, eye tracking). The main duty of the post-holder will be statistical consulting. A broad knowledge of statistics in this scientific area is required. The applicant should have in
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, species-distribution data, ecosystem-condition data, field measurements, or other environmental datasets, using statistical, machine-learning, process-based, or hybrid modelling approaches to analyze
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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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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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management, leading small teams and guiding project assistants Computer literacy and GIS knowledge Modelling experience in spatio-temporal analysis of earth surface processes High level of the English language
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nutritional intervention studies or laboratory experiments (depending on background) Generate, process, and analyze microbiome data, and other multi‑omics datasets Apply machine‑learning models for predicting
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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
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, protein structure modelling, AlphaFold/multimer-based analyses, statistics, data visualization, and interdisciplinary work at the interface of proteomics, structures and machine learning. Track 2
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orientation and strong motivation to make a dissertation Very good knowledge of tTheory and practice of machine learning, e.g. Deep Learning (, Reinforcement learning, and Probabilistic modeling Excellent
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Computer literacy and GIS knowledge Modelling experience in spatio-temporal analysis of earth surface processes High level of the English language in reading, writing and speaking Knowledge of principles