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involving CONEMO (CONtrole EMOcional), a digital, non-pharmacological intervention based on Cognitive Behavioral Therapy (CBT) and designed to require minimal professional support. This pragmatic, prospective
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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
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position within a Research Infrastructure? No Offer Description Activities and context: The fellow will develop machine-learning interatomic potentials (MLPs), trained on density functional theory-DFT data
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chromatography. The candidate will prepare samples for immunopeptidomics by liquid chromatography coupled with mass spectrometry tandem (LC-MS/MS), analyze large datasets, and develop scripts and machine learning
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; • Familiarity with statistical analyses and modeling as well as machine learning approaches, supported with strong skills in computational optimization of methods; • Experience working with large-scale datasets
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to staff position within a Research Infrastructure? No Offer Description Activities: The post-doctoral researcher will develop machine learning models to evaluate the effectiveness and cost
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, engaging with financial institutions that drive the expansion of rural credit. Additionally, they will develop an original analytical framework based on a comparative matrix of research data regarding
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related to staff position within a Research Infrastructure? No Offer Description Activities and context: This project based at the Institute of Biosciences of the University of São Paulo (IB-USP, Brazil
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy
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area: Development of bioinspired antioxidants based on betalain molecular scaffolds; reactivity toward reactive oxygen/nitrogen species and electronically excited (triplet) states; photobiological