Postdoctoral Fellow: Integrative cryo-electron tomography data mining
Your role
- Develop algorithms to identify macromolecular complexes in cellular tomograms, using image processing techniques such as template matching and machine learning
- Investigate and implement methods to enhance the speed and accuracy of particle identification by increasing algorithm efficiency, refining scoring functions, and applying the latest deep learning techniques in computer vision
- Explore the integration of spatial constraints from other data sources to improve particle identification
- Co-develop PyTME (https : / / github.com / KosinskiLab / pyTME)
- Disseminate your code in well-organized, documented, and rigorously tested software packages
- Use these new methods for research projects within the TransFORM consortium
Apply now
Closing date : 19 August 2024
Contract duration : 3 years (with possibility of extension up to 5 years)
Grading : Stipend
Reference number : HH00228
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You have
- Ph.D. in Computer Science, Image Processing, Computational Structural Biology, or a related field
- Advanced programming skills in Python and a proven track record in the development and application of computational tools
- Proficiency in numerical libraries such as NumPy and SciPy
- A solid foundation in mathematics and experience in algorithm development
- At least basic knowledge of machine learning techniques
- Experience in the dissemination and management of software packages
- Strong motivation to work in a highly collaborative and multidisciplinary environment of EMBL and the TransFORM consortium
You might also have
- Experience in cryo-ET data analysis or machine learning. However, candidates with a strong background in either computer science (and a willingness to learn cryo-ET data analysis) or cryo-ET (with proven extensive programming expertise) are encouraged to apply.
- Experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
Postdoctoral Fellow: Integrative cryo-electron tomography data mining
However, candidates with a strong background in either computer science (and a willingness to learn cryo-ET data analysis) or cryo-ET (with proven extensive programming expertise) are encouraged to apply. Experience in cryo-ET data analysis or machine learning. Explore the integration of spatial con...
Postdoctoral Fellow: Integrative cryo-electron tomography data mining
However, candidates with a strong background in either computer science (and a willingness to learn cryo-ET data analysis) or cryo-ET (with proven extensive programming expertise) are encouraged to apply. Experience in cryo-ET data analysis or machine learning. Explore the integration of spatial con...
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