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data collection using the SigCap Application. Data processing and analysis in Python. Assess how environmental conditions and context (weather, indoor/outdoor settings) influence reception quality
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discovery through user research, prototyping, and experimentation to validate solutions that are feasible, usable, and valuable Write production-quality code in Python/Django and JavaScript/React/Vue while
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analysis or modelling tools—such as Aspen Plus, Matlab/Python, or similar—to help link experimental findings to process or techno‑economic evaluations. What you will do Take courses at an advanced level
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Polarization Lab for scientific research on human-AI interaction on social media. The ideal candidate will possess advanced knowledge of R and/or Python software, have experience performing statistical analyses
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and/or machine learning Interest in biology or molecular biology, microbial ecology Proficiency in programming languages such as Python, R and/or C++ as well as Linux systems. Fluency in spoken and
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methodological training in (bio)statistics and/or machine learning Interest in developing rigorous methods for biomedical, clinical, or public health data Experience with statistical computing (R and/or Python
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in machine learning and/or advanced analytical methods, experience working with complex or large-scale datasets, and strong programming skills (e.g., Python or R). You will be able to communicate
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software (e.g. ArcGIS, QGIS) and coding environments (e.g. Python or R), collaborating across LUMHR themes, and supporting interdisciplinary research activity. Teaching support may be required, up to a
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of using Python or R Very good written and spoken English (min. B2) In addition, the following criteria are desirable: basic knowledge of analytical chemistry, neurobiology, or behavioural ecology Experience