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Archiv-Übersicht     Angebot Nr. 14193

Angebotsdatum: 18. März 2021
Art der Stelle: Doktorarbeit
Fachgebiet: Biologie > Biophysik
Titel des Themas: Deep Learning for Superresolution Microscopy

Institut: CCTB, Uni Würzburg
Adresse:
Prof. Philip Kollmannsberger
Campus Hubland Nord 32
97074 Würzburg
Tel.: +499313182375   Fax.:
Bundesland: Bayern
Homepage: http://www.biozentrum.uni-wuerzburg.de/cctb/research/computational-image-analysis/phd-postdoc-position/
E-Mail Kontakt: mail

Beschreibung: We are looking for a highly motivated candidate with a master’s degree in biology, physics, computer science or a related discipline, with a solid background in image processing and quantitative data analysis. Knowledge of at least one programming language and basic statistics is required. Ideally, you already have experience with machine learning and deep neural networks. If your background is not biology, you should have demonstrated interest to apply your computational skills to biological questions (e.g. in your undergraduate research).

In this DFG-funded research project, you will combine deep learning and particle averaging to improve the performance of single molecule localization microscopy, in collaboration with the Sauer Lab (inventor of dSTORM) at the Biocenter of the University of Würzburg.

You will have access to high-end computational resources, including virtual workstations with GPUs for deep learning. The Center of Computational and Theoretical Biology is a young and dynamic research unit within the Faculty of Biology at the University of Würzburg and provides excellent working conditions in a highly vibrant interdisciplinary environment. In our group, we develop and apply computational tools to analyze, quantify, and understand biological image data (“Bioimage Bioinformatics”), in close collaboration with experimental groups within the faculty.

The University of Würzburg is an equal opportunity employer. As such, we explicitly encourage applications from qualified women. Severely handicapped applicants will be given preferential consideration when equally qualified.
Methoden:
Anfangsdatum: 18. März 2021
Geschätzte Dauer: 3 years
Bezahlung: TV-L (65%)
Papers:
Sonstiges:

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