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Vector, Vue.js 3, Node.js, Python, and JSON; Natural Language Processing (NLP) applied to collections; implementation of data pipelines using AI models, embeddings (RAG), and OCR; demonstrated knowledge in
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the environment, including: i) Knowledge of programming languages (e.g., Python and/or R); ii) Ability to work in an interdisciplinary team; iii) Good oral and written communication skills; iv) Strong
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, PRS, pathway analysis, or Mendelian randomization) and statistical analyses in R or Python; the candidate must have programming skills, ability to handle large datasets, experience in scientific
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multiple access. The focus will be on the application of AI techniques, aiming at their reliable, robust, and effective integration. Requirements: - Experience with the Python programming language
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, graphs); experience with analysis and processing of large volumes of data; development of reproducible scientific software; proficiency in Python and libraries (Pandas/NumPy and PyTorch/TensorFlow/Scikit
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Python and R; - Demonstrable experience with Machine Learning; - Excellent problem-solving skills and the ability to work both independently and as part of a team. This position is for full-time, on-site
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planted forests; • Experience in data analysis (R or Python); • Fluency in scientific English; • Valid driver’s license; • Availability to reside in Piracicaba. Applications: via the link https://forms.gle
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, Stata, Python, etc.); • Experience with spatial analysis or georeferenced data (considered a plus); • Interest in public security policies. Application Period: January 26 to February 15, 2026 Link
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annotation; proficiency in R or Python; and excellent English. Experience with spatial transcriptomics and immunology of autoimmune diseases is desirable. Interested candidates should send a motivation letter