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or equivalent approaches. Automated experimental testing, instrument control or data acquisition using tools such as LabVIEW, Python or MATLAB. Pre-employment checks and declarations Your employment is
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Classification Title: Post-Doctoral Associate in unsupervised and generative ML for chemistry Classification Minimum Requirements: PhD in Chemistry or related area Strong coding (Python) and
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. Integration of physiologic waveform features with clinical metadata and outcomes. Creation of reproducible Python and/or MATLAB pipelines for clinical signal processing and analysis. Translation
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. Documented research experience in modern deep learning (e.g. generative models, Bayesian deep learning or large pre-trained models) and excellent programming skills in Python and a modern deep learning
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publications in the field. Required skills include operation and alignment of custom laser instrumentation, and programming experience in e.g. MATLAB/Python/LabVIEW for data analysis and software experimental
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in programming and simulation tools such as Python, MATLAB/Simulink, and/or ML frameworks (TensorFlow, PyTorch) Experience with physics-based modeling Strong analytical and problem-solving skills, with
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architectures; • strong programming skills in Python and experience with a deep-learning framework such as PyTorch, including training and evaluating models on GPU/HPC infrastructure; • experience working with
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instrumentation. Experience with Python, model/API integration, retrieval-augmented generation, tool-using agents, scientific databases, and automated experimental platforms is highly desirable. The candidate is
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statistical software (R, Python, SAS, or similar); English proficiency for reading, writing, and presenting; full-time residence in Piracicaba. Desirable requirements Experience with large datasets and metadata
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microscopy, optogenetics, or in vivo imaging techniques. Experience with electrophysiological recording methods, including patch-clamp techniques. Programming and data analysis experience using MATLAB, Python