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complementary and synergic methods at the intersection of Artificial intelligence, Machine learning, Numerical simulation, Formal verification. Such methods include, among the others: AI-guided simulation
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 1 month ago
of Porto, at Salomé Pinho´s lab. Scientific Area: Immunology, Biochemistry, Glycobiology, Carbohydrates, Biophysics 1. Project summary and work plan GLYCOCALYX (https://www.glycocalyx.org/ ) brings together
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Infrastructure? No Offer Description Grantor: European Union HORIZON Marie Sklodowska-Curie Action (MSCA) Joint Doctoral Network Project portal: https://www.eu4greenfielddata.eu/ Highlights Duration: 1 Sep, 2026
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image analysis. 3. Proteomic assays, including the purification of extracts enriched in micronuclei. 4. Quantitative data analysis using R and formal statistical methods. 5. Support in the setup and
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project Socio-Spatial Situatedness of Roman Professions and its Impact on Religion in the Roman Empire: A Formal Modeling Approach (SIPROME). The SIPROME project investigates how professions and the socio
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complies with the legal requirements for the formalization of the contract in accordance with the Spanish labor law. To be eligible, candidates must officially apply in parallel to: https://www.unimedizin
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, and datasets; often at substantial computational and environmental costs. This PhD project targets sustainable and resource-efficient machine learning with a focus on methods that reduce compute, energy
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of Pisa) and Dr. Stan Van Gisbergen (SCM, Holland) https://www.scm.com/ , who will also serve as industrial mentor. DC9 - Objectives: Apply Machine Learning force fields and sampling methods to model bio
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27, 2026. 16.2. Applications must be formalized in the online application submission system, available on the FMUP website: https://sigarra.up.pt/FMUP/pt/CNT_CAND_GERAL.CONCURSOS_LIST (Ref. 2026/10
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methods of linguistic data collection and analysis and can therefore use these methods in a critical and reflective way. All doctoral students will receive individual supervision from two faculty members