Bern, Berne, Switzerland
Materials Scientist and Physical Engineer specialized in graphene and low-dimensional materials. Strong background in data analysis, statistics and computational modeling of complex systems. Passionate about nanoscience and nanotechnology, excellent analytical skills and very good at finding creative solutions to complex problems. Thrives working individually and in teams. • 8 years of experience in Research and Development (R&D): novel functional materials for micro and nanotechnology used in a wide range of applications across many sectors (energy, horology, automotive, biomedicine) • 8 years of experience in computational modeling and simulation of advanced materials: from quantum-mechanical models to macroscopic/continuum approaches • 5 years of Lab experience with development and characterization of materials and surface analysis techniques
• Predictive modelling: use historical data to predict performance deterioration and structural health state of gas turbine engines and compressors • Set-up and maintenance of monitoring and diagnostic systems for power plants, automatic trend monitoring and reporting • Provide extended engineering support for Plant Support topics for performance and combustion • Data analysis and limit adjustment using remote monitoring tools • Formulate techniques for quality data collection and data management to gas turbine services in close collaboration with, product management, engineering and R&D
• R&D in graphene-based devices for nanotechnology (power generation, batteries, MRAM storage, touch screens, sensors for horology applications) • modeling and computational simulation of graphene and other low-dimensional carbon materials (carbon nanotubes, fullerenes, diamond thin films) using advanced computational methods (molecular dynamics, Monte Carlo methods, DFT) • systematic characterization of the morphology (AFM, SEM), microstructure (XRD, Raman), chemical-components (XPS, AES) and electronic/magnetic properties (PAC) of graphene with atomic/molecular species adsorbed on the surface • data analysis (MATLAB and Python) and data visualization of experimental data • design and setup of an ultra-high vacuum apparatus to grow up (CVD and MBE) 2D-materials and thin films, atomic deposition of other species and perform surface-characterization (AFM, AES and PAC)
• modelling and computational simulations using Monte Carlo methods and density functional theory (electronic structure and magnetic properties of different multiferroic materials) • experiments at ISOLDE/CERN using nuclear radioactive spectroscopy techniques to characterize the atomic local environment of multiferroic materials • structural, dielectric and magnetic characterization of different multiferroic samples (SEM, AFM, XPS, Squid) • FEM simulations (COMSOL Multiphysics) and data analysis (MATLAB and Mathematica) to recover analytical trends from experimental datasets