This course is an introduction to the methodological issues of scientific research. The objective is to help doctoral students conduct a scientifically robust research.
This course builds on environmental chemistry and microbiology taken in previous courses. The emphasis is on quantification using the public domain package, PHREEQC, which is an excellent computation
Le cours "Critical Data Studies" s'inscrit dans la nouvelle offre d'enseignements TILT qui propose de croiser des savoirs provenant des SHS et des sciences de l'ingénieur afin d'aborder des thématique
Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analy
Hands on experience doing synchrotron diffraction experiments (i.e. grazing incidence, powder & single crystal diffraction, total scattering, and in-situ or operando experiments)
Learn to process and
Covers development and design of models for materials processes and structure-property relations. Emphasizes techniques for solving equations from models or simulating and visualizing behavior. Topics
An overview of the main concepts and tools of big data, automatisation, and applications of AI in chemistry is presented through lectures and workshops. Specific applications of machine learning to co
Data Think! offers theoretical and practical introduction to data-centric research. Participants learn about collaborative research pipelines, data management plans, data ethics, data visualization an