Postdoc in machine learning for structural bioinformatics

Linköping University

Application deadline

August 15, 2022



Postdoc in machine learning for structural bioinformatics

Linköping University, Department of Physics, Chemistry and Biology

Skilled and committed employees are a crucial factor in the success of Linköping University. And we need more of them. Our core expertise comes from teachers and researchers, but a successful university requires experienced and motivated employees in many fields. Everyone is important. We need to recruit many new employees thanks to, among all, an expansion in our research activity. We need you here. We look forward to receiving your application!

The Department of Physics, Chemistry and Biology conducts research and offers education at undergraduate and postgraduate levels. Research, the predominant activity, is often done in collaboration with corporate and international partners. We are one of the university’s largest, oldest and most well-known departments, encompassing five interacting scientific fields: biology, chemistry, material physics, applied physics and theory and modelling.

We are now looking to appoint a Postdoc in machine learning for structural bioinformatics formally based at the Department of Physics, Chemistry, and Biology (IFM).

Work assignments

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.

This position is part of the post-doctoral research project “Data-driven application to protein-protein interactions”, which is a joint interdisciplinary research project between professor Björn Wallner at Linköping University (Björn Wallner – LiU) and associate professor Alexey Amunts at SciLifeLab (Alexey Amunts – SU) with aim of using and develop AI methods to understand protein-protein interactions and apply them to biologically relevant problems for which we have cryo-EM data. The project involves using existing methods, i.e., AlphaFold, and developing new AI methods that are specific tailored to the problem and the data available. The position is based at the AI structural biology group at LiU, but it also includes extensive collaborations with the cryo-EM group at SciLifeLab.

We are looking for a motivated, independent postdoc researcher in AI and machine learning and/or structural biology eager to learn new methodologies. Central to the project is the development of methods that incorporate experimental data or prior information into the AI methods to improve predictions and modeling capabilities.

The AI structural biology group at LiU is the leading group in structural bioinformatics in Sweden and have contributed with some of the ideas and methodologies that are used in AlphaFold (the use of rawMSA and the DockQ measure). The group is embedded together with experimental groups in structural biology at the department ensuring that the developed methods are relevant and can be readily applied. The current research focus is on how to incorporate protein dynamics and flexibility into the models to enable a deeper understanding on protein function. The group have access to the newly installed Berzelius GPU-cluster. Berzelius is an NVIDIA® SuperPOD consisting of 60 NVIDIA® DGX-A100 compute nodes supplied by Atos. Each DGX-A100 node is equipped with 8 NVIDIA® A100 Tensor Core GPUs, 2 AMD Epyc™ 7742 CPUs, 1 TB RAM and 15 TB of local NVMe SSD storage. The A100 GPUs have 40 GB on-board HBM2 VRAM.

The cryo-EM group at SU consists of three PhD students, and three postdocs. The group has access to the state-of-the-art cryo-EM facility equipped with Titan Krios microscopes with K3 direct electron detectors. The research focus is on large multi-protein complexes involved in bioenergetics. 

The postdoc position offers an opportunity to further develop your research profile, since the majority of your working time is devoted to research.  As a postdoc, you are expected to work independently and to be able to supervise/co-supervise undergraduate and PhD students. Teaching of undergraduate students may also be included, but not more than 20% of the time.

Information about WASP and DDLS:

WASP: 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 Swedish industry. Read more: WASP Sweden.

DDLS: 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 the people´s lives, detecting and treating diseases, protecting biodiversity and creating sustainability. The programme 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: SciLifeLab & Wallenberg National Program for Data-Driven Life Science.

Qualifications

To be qualified to take employment as postdoc, you must have been awarded a doctoral degree or have a foreign degree that is deemed to be equivalent to a doctoral degree. This degree must have been awarded at the latest by the point at which LiU makes its decision to employ you.

It is considered advantageous if your doctoral degree is no older than three years at application deadline for this job. If there are special reasons for having an older doctoral degree – such as taking statutory leave – then these may be taken into consideration.

We are seeking applicants who have a Ph.D. degree in a relevant area, such as bioinformatics, computer science or structural biology. Previous experience with machine learning, artificial intelligence and/or structural biology is required. The applicant should also be experienced in programming, preferably Python or equivalent language. Strong communicative skills and fluency in written and spoken English are a requirement. Having worked with large data set in HPC environment is also a merit.

About this job

This post is a temporary contract of two years with the possibility of extension up to a total maximum of three years. The position as a postdoc is full-time.

Starting date: As soon as possible.

Salary: Salaries at the university are set individually. State your desired salary in the application. The salary budget for this position is much higher than for a regular postdoc position. 

More information about employee benefits is available here.

Trade union representatives

Information about trade union contacts can be found here.

Application procedure

Your application must reach Linköping University no later than 15 August 2022. Applications received after the deadline will not be considered. 

We welcome applicants with different backgrounds, experiences and perspectives – diversity enriches our work and helps us grow. Preserving everybody’s equal value, rights and opportunities is a natural part of who we are. Read more about our work with equal opportunities.

We look forward to receiving your application!

Linköping university has framework agreements and wishes to decline direct contacts from staffing- and recruitment companies as well as vendors of job advertisements.

Contact persons

Björn Wallner, Professor, +46 13 28 27 59, bjorn.wallner@liu.se

Ref IFM-2022-00225

Last updated: 2022-07-05

Content Responsible: Anna Frejd(anna.frejd@scilifelab.se)