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well as to the geometric optimization of the separator, including the swirl generator. Mandatory requirements PhD in mechanical, naval or aerospace engineering, or a related field. Proven experience in numerical simulation
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. Randomization, participant training, and implementation of the intervention. Mandatory requirements: PhD obtained within the past 7 years, with degree completion by January 2027. Availability to conduct the post
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, generalized transverse-momentum-dependent distributions (GTMDs), and electromagnetic and gravitational form factors, using continuum dynamical methods. Mandatory requirements: Ph.D. in Nuclear Physics, Hadron
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: Computer Science or Computer Engineering; • PhD: Computer Science or related fields within the last 7 years; • Knowledge of: Python, DL, CV, Transformers, LLMs, NLP; • Relevant scientific publications; • English
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, microstructure, and properties. Data analysis and preparation of scientific papers, reports, and conference contributions. Mandatory requirements: PhD in Materials Engineering, Metallurgical Engineering, or
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requirements: PhD obtained less than seven years ago in Chemistry, Materials Science/Engineering, Chemical or Biomedical Engineering, Biotechnology, or a related field. Proven experience in electroanalysis and
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cities and databases. Mandatory requirements: PhD in engineering, data science and computing, mathematics, or statistics; experience in engineering, data science and computing, mathematics, or statistics
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, statistical analyses (including multivariate approaches), and scientific writing. Mandatory requirements: PhD in physiology, ecology, neuroendocrinology, molecular biology, or related fields. Strong experience
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, public land management, or urban and housing regulation. They must hold a PhD awarded within the past seven years, have an outstanding graduate academic record, be available for full-time, on-site research
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recipient will contribute to the core research theme of the RATIONAL project, which focuses on investigating and developing robust evidence-based retrieval methods for Natural Language Inference (NLI) tasks