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27 Jan 2026 Job Information Organisation/Company FAPESP - São Paulo Research Foundation Research Field Medical sciences Researcher Profile Established Researcher (R3) Application Deadline 20 Feb 2026 - 23:59 (UTC) Country Brazil Type of Contract To be defined Job Status Not Applicable Is the job...
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essential for patient care and direct communication. Requirements: - Bachelor's degree in a Life Sciences field and PhD defended within the last seven years in Molecular Biology or Medical Physiopathology
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potential use of the Tietê–Paraná Waterway. 3) Solving problems associated with the definition of regular navigation services. 4) Modeling and solving the lock transit scheduling problem. Requirements: • PhD
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-industrial residues from Brazil and Chile. The candidate must hold a PhD in Biotechnology, Pharmacy, Food/Chemical/Bioprocess Engineering, or related fields. Proven expertise is expected in chromatographic
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patterns, and alternative integrated and humanized approaches to public security. Requirements: • Completed PhD in any field; • Knowledge of advanced statistics and at least one programming language (R
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Research Foundation (FAPESP). Requirements: • Completed PhD in any field; • Experience in comparative public policy analysis; • Experience with qualitative and quantitative methods; • Intermediate knowledge
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, analyzing how these movements position themselves within power relations and climate action networks, articulating knowledge, subjectivities, and public policies. The post-doctoral researcher will adopt
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; - Supervise students. Requirements: • Fluency in English; • Experience with germination experiments and trait measurements; • Knowledge of statistics and data analysis using R; • Willingness to reside in Rio
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staff position within a Research Infrastructure? No Offer Description We are looking for a PhD in Chemistry, Chemical Engineering, or Petroleum Engineering to join a postdoctoral project focused on
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. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness