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14 Jul 2026 Job Information Organisation/Company FAPESP - São Paulo Research Foundation Research Field Computer science Researcher Profile Established Researcher (R3) Application Deadline 9 Aug 2026 - 23:59 (UTC) Country Brazil Type of Contract To be defined Job Status Not Applicable Is the job...
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involving large companies under the “Autonomous Systems, Robotics, and Machine Tools” track of the IASMIN Platform (a FAPESP Applied Research Center in AI). The work is to be carried out on-site
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and the Brazilian coast. Research proposals must be positioned at the interface between biological oceanography and physical oceanography, with a particular focus on physical–biological coupling
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computing, obtained within a maximum of 7 years; application of machine learning and deep learning methods to remote sensing images; proficiency in programming (R, Python, or similar); ability to work
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: Experience with electrochemical techniques applied to the characterization of interfaces and charge-transfer processes; nanostructured materials and thin films; surface functionalization and aptamer, antibody
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machine learning algorithms to support the traceability of the beef’s geographical origin. She/he will participate in all stages of the project, including planning and supervision of sample collection and
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networks, from a machine learning and information theory perspective. This basic research project has strong translational potential and aims to elucidate how immune function is altered during sepsis, with
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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