Postdoc in Machine Learning

Work assignments

The research focus for the open position is to develop new machine learning methodology for novel materials discovery. You will be part of the KAW-funded cross-disciplinary project The 2D Materials Frontier. In collaboration with world-leading physicists in Linköping and Uppsala, we will develop machine learning methods to aid in the quest for new ultra-thin materials, with applications in energy storage, catalysis, and water treatment, to mention a few.

Machine learning, in particular methods based on graph neural networks and geometric deep learning, have recently shown great potential to enable major leaps in the field of data-driven materials science, and to significantly speed up the search for new materials. However, for ultra-thin materials we face numerous challenges related to unique structures, material properties, target variables, data availability, etc. These challenges require novel machine learning methodology to be developed, and it is the goal of this position to contribute to such development.

While the research focus is on machine learning methods and theory, you will also get the opportunity to work in a unique cross-disciplinary environment together with some of the world-leading experts on 2D materials. You will work in close collaboration with both experimental and theoretical physicists who will contribute with domain expertise, and you will have the opportunity of applying the machine learning methods developed in the project in practice to aid in the quest for novel 2D materials.

As postdoc, you will principally carry out research. A certain amount of teaching may be part of your duties, up to a maximum of 20% of working hours. Teaching will in that case be at basic or advanced level for courses in machine learning, programming and/or statistics. The duties also include contributing to the scientific discussion at the department, for instance by participating in and organizing reading groups and seminars and engaging in PhD supervision. You are expected to actively engage in the collaboration with the different project partners and to serve as a link between the involved departments.

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 when 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 PhD degree in machine learning, statistics, or a related area that is considered relevant for the research topic of the project.

The position requires very good knowledge of spoken and written English. A successful candidate should have a strong background in machine learning, applied mathematics, statistics, computer science or a related area that is considered relevant for the research topic of the project. Scholarly proficiency must have been demonstrated through original research resulting in publications in internationally recognized journals and conferences. Publications in journals in statistics and machine learning, as well as publications at international machine learning conferences, are particularly advantageous. Documented experience with applying or developing machine learning for applications in materials science, physics, or related areas is advantageous. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. The applicant should furthermore have a strong drive towards performing fundamental research; the ability and interest to work in a team; and strong communication skills.

The workplace

Linköping University is one of the leading AI institutions in Sweden. We have strong links to prominent national research initiatives, such as WASP and ELLIIT and you will have access to state-of-the-art computing infrastructure for machine learning, e.g. through BerzeLiUs.

The position is formally based at the Division of Statistics and Machine Learning (STIMA). At STIMA we conduct research and education in both statistics and machine learning, at the undergraduate, advanced and PhD levels. We regularly publish solid contributions at the best machine learning conferences. STIMA is characterized by a modern view of the statistical subject, where probabilistic models are combined with computational algorithms to solve challenging complex problems, as well as a statistical view of machine learning which clearly integrates the two subject areas within the division. For more information about STIMA, please see https://liu.se/en/organisation/liu/ida/stima

STIMA is part of the Department of Computer and Information Science (IDA) – a dynamic, international, and collaborative environment with a strong focus on research, which spans the range from purely theoretical to applied, where the latter is often being conducted in cooperation with industrial partners and other organizations. Read more at https://liu.se/en/organisation/liu/ida

The position is part of the cross-disciplinary project The 2D Materials Frontier, led by Professor Johanna Rosén at the Division of Materials Design at the Department of Physics, Chemistry and Biology (IFM), see https://liu.se/en/organisation/liu/ifm In this project you will be indirectly associated with IFM and, indeed, act as a link between the two departments. IDA and IFM are physically located in neighboring buildings, which simplifies a tight collaboration.

The employment

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
By agreement.

Salary and employment benefits

Salaries at the university are set individually. State your desired salary in the application.

More information about employee benefits is available here.

Union representatives

Information about trade union contacts can be found here.

Application procedure

Apply for this position by clicking on the button labelled “Apply” below. Your application must reach Linköping University no later than November 3, 2023.

Applications received after the deadline will not be considered.