You will work on independent research projects aiming at the development of new segmentation techniques, applying concepts from deep learning and general artificial intelligence to the automated analysis of large sets of cryo electron tomography data.
You will devise, implement and test new methods for extracting high resolution structures from cryoET data sets, integrating new approaches for classification and numerical compensation of imaging aberrations.
You will contribute to the maintenance and visibility of the Dynamo package, presenting it in international conferences and user training workshops.
We welcome applications from numerical scientists or structural biologists with solid skills in Matlab, C++, CUDA and/or Python. Experience in Computer Vision and Deep Learning is highly desirable. A background in Image Processing for CryoEM is a plus. The position will involve constant interaction with end-users of our package; a flair for creating well documented tools ready for the use by a large community of users is thus of the essence.