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/ computer vision and pattern recognition, including but not limited to biomedical applications Strong interest in applied machine learning, including but not limited to deep learning Experience utilising GPU
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy
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assessment of chemical plants using HAZOP analysis Use of process modeling and simulation to enhance quantitative assessments Use of machine learning to support HAZOP discussions with the aim of obtaining a
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years of post-PhD research and engineering experience in AI for mobile security Solid knowledge in adversarial machine learning or trustworthy AI, including experience with robustness assessment and
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, etc.), and data-driven methods (optimisation, generative AI, agent-based modelling, machine learning). Our work provides decision support for policy makers, industry stakeholders, and researchers by
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machine learning approaches to quantitatively analyze experimental data and predict emergent multicellular behaviors under varying mechanical and chemical environments. For more information about our lab
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machine learning or trustworthy AI, including experience with robustness assessment and attack/defense mechanisms. Expertise in software security and code analysis, with understanding of common
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paraganglioma driven by cell plasticity using spatial transcriptomics and machine learning.” High-risk neuroblastoma (NB) and malignant paraganglioma (PPGL) are neural crest–derived tumors with pronounced
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, integrative biology approach that utilizes human pluripotent stem cell based model systems, high throughput functional genomic screening and big data based machine learning, bridging the scales from genetics
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University of Vienna, the PhD program for life scientists and computational scientists/machine learning experts will start in January 2026. The goal of the PhD Program is to address real-world problems in