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Protein structure is essential for understanding their function as well as for developing drugs targeting proteins. Recently, a deep learning method that can predict the structure of most proteins was developed. However, proteins do not act alone, thus, the next major challenge is to predict protein-protein interactions. Despite the recent advances, there are many proteins that cannot be built accurately, nor are we able to always distinguish interacting from non-interacting protein pairs. In this project, we are recruiting two postdocs to leverage recent advances in the field of machine learning to build better deep-learning models for predicting protein-protein interactions and to apply these methods to biologically relevant problems.
Azizpour’s group is part of the KTH division of Robotics, Perception, and Learning. He has extensive experience in computer vision and deep learning. The main research directions pursued in Azizpour’s group have direct relevance to this project which includes robustness and estimation of uncertainty, transfer learning including knowledge distillation techniques, non-standard deep networks e.g., graph networks and transformers, and interpretable deep learning. Furthermore, the group has extensive experience in deploying large experiments in GPU clusters. It consists of 4 Ph.D. students, 1 postdoc, and several master students/interns.
The project is in close collaboration with Arne Elofsson’s group at SciLifeLab.
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.
Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education, and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information, and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems, and software for the benefit of the Swedish industry. Read more: https://wasp-sweden.org/
The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) is a 12-year initiative that focuses on data-driven research, within fields essential for improving people´s lives, detecting and treating diseases, protecting biodiversity, and creating sustainability. The program will train the next generation of life scientists and create a strong computational and data science base. The program aims to strengthen national collaborations between universities, bridge the research communities of life sciences and data sciences, and create partnerships with industry, healthcare and other national and international actors. Read more: https://www.scilifelab.se/data-driven
Read more about what it is like to work at KTH
Requirements
Preferred qualifications
As a person, you are creative and work with great independence. It's important that you can collaborate both with colleagues as well as external partners. Great emphasis will be placed on personal competency.
You will find contact information to trade union representatives at KTH's webbpage.
Log into KTH's recruitment system in order to apply to this position. You are the main responsible to ensure that your application is complete according to the ad.
Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).
The position offered is for, at the most, two years.
A position as a postdoctoral fellow is a time-limited qualified appointment focusing mainly on research, intended as a first career step after a dissertation.
Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.
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Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.
Type of employment | Temporary position |
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Contract type | Full time |
First day of employment | According to agreement |
Salary | Monthly salary |
Number of positions | 1 |
Full-time equivalent | 100% |
City | Stockholm |
County | Stockholms län |
Country | Sweden |
Reference number | J-2021-3068 |
Contact |
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Published | 16.Dec.2021 |
Last application date | 28.Feb.2022 11:59 PM CET |