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Responsibilities Work closely with the PI, Co-PI, and research team to ensure timely completion of all project deliverables. Implement and enhance GeoTOPSIS/VectorMCDA algorithms within QGIS using Python
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. The key objective is to support efforts to advance fundamental and high-impact research. For more details, please view http://www.ntu.edu.sg/spms . Join the laboratory of Shilei Ding at SPMS. We are seeking
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, diesel generators, and other sources. Implement predictive, rule-based, or optimisation-based control strategies using MATLAB/Simulink, Python, or embedded software tools. Integrate controller logic with
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diverse operating systems; Skills in scientific programming (e.g. Python, MATLAB) and the application of advanced data visualization techniques; Very good command of Polish and English, both written and
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). Conduct in vivo optical imaging experiments on healthy volunteers and patients; Develop image-analysis pipelines (Python, MATLAB) and model functional optical signals; Optimize and maintain the AO-RSO
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transcriptomics data and network-theoretic approaches. - design of a new mathematical method - monitoring and study of publications relevant to the field - programming/coding in Python (Pytorch) - presentation
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dashboards • Design and implementation of a web dashboard for visualizing energy consumption on an urban scale. • Use of tools such as Python (Dash, Flask), JavaScript, Plotly, Mapbox, Leaflet, or equivalent
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Programme (PEPR) Forest Resilience (FORESTT – https://www.pepr-forestt.org/ ), funded by the French Plan d'Investissement d'Avenir (PIA) France 2030. FORESTT aims to support the transition of forest socio
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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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, brings together around 300 people and is one of the leading centers for fundamental research in biology in the Paris region. The host team (https://www.ijm.fr/recherche/duharcourt-lab-vf/ ) is particularly