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Applied materials science

Tasks: ·Develop preprocessing, calibration, classification, regression, and validation workflows for Mid-Infrared spectral data ·Assess data quality, experimental design, sampling strategy, confounding factors, and model robustness ·Build reproducible chemometric pipelines using open-source tools and documented code ·Compare modelling approaches and define fit-for-purpose performance metrics and acceptance criteria ·Work closely with optics, engineering, software, biology/diagnostics, and project stakeholders ·Translate research methods into practical, maintainable solutions suitable for a product-development environment ·Document datasets, assumptions, methods, validation results, limitations, and recommended next steps ·Support knowledge transfer and help establish an internal chemometrics capability ·Contribute to external collaborations with universities, research groups, or specialist partners when appropriate Education/Experience: ·Degree in bioinformatics, mathematics, data science, statistics, chemometrics, or analytical chemistry, or a closely related discipline ·4 + years of hands-on experience with chemometrics ·Programming capability in Python and/or R, including reproducible, version-controlled data analysis ·Experience with model validation, cross-validation, data leakage prevention, uncertainty, and interpretation of results ·Preferred: experience applying chemometrics to Mid-Infrared, NIR, Raman, or comparable spectroscopy data ·Preferred: experience in diagnostics, medical devices, life sciences, or regulated product development ·Preferred: knowledge of spectral preprocessing, calibration transfer, feature selection, and domain adaptation ·Proficiency in English; German is an advantage