Implementation of Machine and Deep learning tools for data and image analysis.

- Data analysis and image treatment of scientific data using Machine Learning and state of the art Deep Learning techniques. Use of most programming languages for scientific programming with focus on Python and major libraries like scikit-learn, SciPy, Pandas for statistical analysis ( clustering, suppor vector machine, principal component analysis, random forest) and Deep Learning frameworks such as Pytorch.- Several scientific project• Computer vision algorithms for automatic thickness identification of 2D materials.• Machine Learning and Deep Learning with publications in peer reviewed journals for tomographic images.• Collaboration with Biology department for developing automatized image analysis tools using Machine Learning techniques. Numerical modelling of ordinary differential equations to describe living systems using high-performance computing techniques (GPUs)-Introduction to Python for bachelor students (EN and FR)

- Data analysis and image treatment of scientific data using Machine Learning and state of the art Deep Learning techniques. Use of most programming languages for scientific programming with focus on Python and major libraries like scikit-learn, SciPy, Pandas for statistical analysis ( clustering, suppor vector machine, principal component analysis, random forest) and Deep Learning frameworks such as Pytorch.- Several scientific project• Study of electronic properties of 2D materials with topological properties.• Computer vision algorithms for automatic thickness identification of 2D materials.• Machine Learning and Deep Learning with publications in peer reviewed journals for tomographic images.• Collaboration with Biology department for developing automatized image analysis tools using Machine Learning techniques. Numerical modelling of ordinary differential equations to describe living systems using high-performance computing techniques (GPUs)-Introduction to Python for bachelor students (EN and FR)