I have been analysing images from various life science areas for 13 years now, and currently I am an image processing specialist and data analyst for multiple faculties of Bern University. I help scientists figuring out how to extract information from their images coming from a large variety of techniques such as fluorescence microscopy and electron microscopy, and greatly enjoy the opportunity to constantly learn about new research areas.

For this work, I develop scripts to automatize repetitive tasks for image processing tools (Fiji, Imaris, Chimera) and for larger projects I write custom code in Python that scientist can run in Jupyter notebooks exploiting the power of local computer clusters or cloud services (SwitchEngine, Amazon AWS, Google Compute Engine). While of course I use classical approaches of image processing (filtering, morphological operators etc.), I also have a strong interest in applying machine learning methods and in particular deep learning approaches (convolutional neural networks in particular) for image enhancement and segmentation. I also enjoy teaching these methods interactively and created courses that are openly available (see e.g. https://github.com/guiwitz/Python_image_processing).

Previously, I studied physics at EPFL and turned myself into a microbiologist during postdoctoral studies at Harvard University and the Biozentrum Basel. I found it immensely enriching to be able to perform studies from A to Z, starting from the genetic manipulations to create bacterial strains, continuing with the development of microfluidics devices to perform live imaging of these bacteria, and ending with the development of an image processing and data analysis pipeline. This experience is crucial to allow me now to help other scientist optimising their own projects to extract the best out of their experiments.