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Field
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modelling; strong programming and research engineering ability (Python with modern ML tooling such as PyTorch/JAX) and good software practices; familiarity with interactive/agentic settings (e.g., tool-using
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Posting Description POSTDOCTORAL ASSOCIATE, Chemistry, will lead design and development of an open-source Python-based package for the prediction and analysis of spectroscopic data, primarily
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physics. Familiarity with scientific programing languages such as python. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected
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programming languages such as R or Python Experience with multiome data analysis (e.g. methylomics, Lipidomics, Proteomics, ATAC-seq) Proven experience with advanced computational methods such as deep and
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experience, preferably in Python or R, and experience in the Linux environment Solid publication record in peer-reviewed journals. Proficient in verbal and written English. Excellent teamwork
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: Proficient in Python. Machine Learning: Strong experience with frameworks like TensorFlow, Keras, or PyTorch. Preferred Skills: Experience with Explainable AI (e.g., SHAP, Integrated Gradients
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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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Architectures Demonstrated ability and interest in working across methodological boundaries Solid programming skills (e.g. Python) and experience with research-oriented software development Evidence of research
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communication skills in English, 4. Programming skills are desirable (Julia, Python, convex optimization and semidefinite programming). Task description: The project focuses on analytic and geometric properties
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engine dynamometer experiments, including instrumentation, data acquisition, and test planning Develop and maintain physics-based modeling tools, including custom solvers written in MATLAB, Python, Fortran