Postdoctoral Fellow in Biophysics with focus on machine learning
The Department of Biochemistry and Biophysics is one of the biggest departments at the Faculty of Science with about 150 employees and 2,000 students. The department has world-leading research in cell and molecular biology, in particular within structural biology, molecular modeling/simulation and cryo-electron microscopy. This position is part of a joint collaboration between the two largest research programs in Sweden, the Wallenberg AI, Autonomous Systems and Software Program (WASP) and the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), with the ultimate goal of solving ground-breaking research questions across disciplines.
Cryo-electron microscopy (cryo-EM) has been a revolution for structural biology with its ability to computationally recover the 3D electron density of proteins based on millions of noisy images of single protein molecules. In some cases, modern reconstruction methods have also made it possible to predict flexibility of molecules, but only on coarse scales. This postdoctoral project is a collaboration with the math department at KTH, where we will use the massive amounts of data on protein motion available in molecular simulations produced in our team to develop new neural networks to provide data-driven priors of atomic models used to predict both structure and motion from new cryo-EM data we collect at SciLifeLab.
You will work together with mathematicians, structural biologists and computational chemists on performing molecular simulations and developing new ways to describe and featurize molecular motions both in cryo-EM data and simulations. You will be involved in training and testing networks, and in particular assess the performance of multiscale motion predictions on new cryo-EM data.
Postdoctoral positions are appointed primarily for purposes of research. Applicants are expected to hold a Swedish doctoral degree or an equivalent degree from another country.
The degree must have been completed at latest before the employment decision is made, but no more than three years before the closing date. An older degree may be acceptable under special circumstances. Special reasons refer to sick leave, parental leave, elected positions in trade unions, service in the total defense, or other similar circumstances as well as clinical attachment or service/assignments relevant to the subject area.
In the appointment process, special attention will be given to research skills within the field. Knowledge and experience of simulations, computational cryo-EM reconstruction, or deep learning frameworks, such as PyTorch or TensorFlow, is a strong merit.
Terms of employment
The position involves full-time employment for a minimum of two years and a maximum of three years, with the possibility of extension under special circumstances. Start date 2022-07-01 or as per agreement.
Stockholm University strives to be a workplace free from discrimination and with equal opportunities for all.
Further information about the position can be obtained from the project leader, Professor Erik Lindahl, firstname.lastname@example.org.
Ingrid Lander (Saco-S), telephone: +46 708 16 26 64, email@example.com, Alejandra Pizarro Carrasco (Fackförbundet ST/Lärarförbundet), telephone: +46 8 16 34 89, firstname.lastname@example.org, and email@example.com (SEKO).
Apply for the position at Stockholm University’s recruitment system. It is the responsibility of the applicant to ensure that the application is complete in accordance with the instructions in the job advertisement, and that it is submitted before the deadline.
Please include the following information with your application
- Your contact details and personal data
- Your highest degree
- Your language skills
- Contact details for 2–3 references
and, in addition, please include the following documents
- Cover letter
- CV – degrees and other completed courses, work experience and a list of publications
- Research proposal (no more than 3 pages) describing:
– why you are interested in the field/project described in the advertisement
– why and how you wish to complete the project
– what makes you suitable for the project in question
- Copy of PhD diploma
- Letters of recommendation (no more than 3 files)
- Publications in support of your application (no more than 3 files).
The instructions for applicants are available at: How to apply for a position.