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Field
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learning and AI methods are preferred Strong skills in R and/or Python. An interest in conceiving and designing new projects, in line with the groups’ research focuses. A proven track record showing
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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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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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or Python. With desirable skills include experience with culturing unicellular eukaryotes and comparative genomics. You will hold strong communication skills and effective collaboration, with demonstrable
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, Python) for data analysis and visualization. Excellent communication skills, both written and verbal, with a proven ability to work collaboratively in a team environment. Experience mentoring trainees is
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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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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
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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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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