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Position: PhD student
Institution: Universität Basel
Department: Biozentrum
Location: Basel, Switzerland
Duties: You will work on independent research projects aiming at the development of new segmentation techniques, applying concepts from deep learning and geneal 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
Requirements: 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
   
Text: PhD student 100% The Biozentrum of the University of Basel is one of the leading institutes worldwide for molecular and biomedical basic research and teaching. It is home to more than 30 research groups with scientists from over 40 countries. Research at the Biozentrum focuses on the areas of Cell Growth & Development, Infection Biology, Neurobiology, Structural Biology & Biophysics and Computational & Systems Biology. With its more than 500 employees, the Biozentrum is the largest department at the University of Basel's Faculty of Science. A position is available to work in the scientific development and technical maintenance of the Dynamo package for tomography and subtomogram averaging ( www.dynamo-em.org ). Your position You will work on independent research projects aiming at the development of new segmentation techniques, applying concepts from deep learning and geneal 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. Your profile 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. We offer you This position is funded for four years and immediately available. We offer an exciting and stimulation work environment with granting access to outstanding resources for data analysis and acquisition. For further scientific information see Dynamo: A flexible, user-friendly development tool for subtomogram averaging of cryo-EM data in high-performance computing environments. Castaño-Díez D, Kudryashev M, Arheit M, Stahlberg H., J Struct Biol. 2012. Dynamo Catalogue: Geometrical tools and data management for particle picking in subtomogram averaging of cryo-electron tomograms. Castaño-Díez D, Kudryashev M, Stahlberg H., in J Struct Biol. 2017 Feb; 197(2):135-144 The Dynamo package for tomography and subtomogram averaging: components for MATLAB, GPU computing and EC2 Amazon Web Services. Castaño-Díez D. in Acta Crystallographica Section D: Structural Biology 73 (6). Application / Contact Please send your complete application (including cover letter, CV, reference letters, diplomas) to daniel.castano@unibas.ch . For informal enquiries, please contact Daniel Castano, e-mail: daniel.castano@unibas.ch . www.unibas.ch
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