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 ()
- Disseminate your code in well-organized, documented, and rigorously tested software packages
- Use these new methods for research projects within the TransFORM consortium
Closing date : 19 August 2024
Contract duration : 3 years (with possibility of extension up to 5 years)
Grading : Year 1 stipend - €4,010 per month after tax
Reference number : HH00228
Related
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...
Postdoctoral Fellow: AI-based integrative modeling of macromolecular complexes
Develop computational methods to model the atomic structure of large macromolecular complexes using tools such as AlphaFold, RoseTTAfold, and OpenFold, alongside your own innovative AI-based algorithms, and integrating experimental data from in-cell cryo-ET tomography and crosslinking mass spectrome...
Postdoctoral Fellow: AI-based integrative modeling of macromolecular complexes
Develop computational methods to model the atomic structure of large macromolecular complexes using tools such as AlphaFold, RoseTTAfold, and OpenFold, alongside your own innovative AI-based algorithms, and integrating experimental data from in-cell cryo-ET tomography and crosslinking mass spectrome...
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