PhD in Materials Science

Join us in developing machine-learning accelerated simulation methods to understand and optimize interfaces in hybrid organic-inorganic materials for sustainable energy devices.

Your work assignments

The doctoral student will computationally understand and optimize interfaces in hybrid (organic-inorganic) materials for sustainable energy devices. Material interfaces are often the limiting factor for device performance and stability, since they must sustain both electronic and ionic transport simultaneously. This is the case, for example, at electrode/electrolyte interfaces in organic batteries, where ion transport governs charging and discharging, and at interfaces in solar cells, where ion migration through structural defects drives degradation and can enhance recombination losses. Resolving how this coupling between electronic and ionic transport depends on atomistic interface structure, and how it evolves under operating conditions, is difficult to access experimentally and lies beyond the reach of standard simulation methods.

This PhD topic falls within the area of computational materials science and will involve the use of established methods such as density functional theory and molecular dynamics, as well as the development of machine-learning potentials and Hamiltonians for fast ion transport and electronic structure predictions, respectively. Your specific tasks are:

Develop machine learning potentials and Hamiltonian learning approaches for organic-inorganic interfaces, such as organic battery electrode/electrolyte interfaces and defect-containing solar cell interfaces

Perform molecular dynamics simulations of interfacial ion transport and understand the evolution of the electronic structure under realistic operating conditions

Contribute to the design of stable material interfaces for efficient charge and ion transport with focus on organic batteries and solar cells

Collaborate with experimental and theoretical groups within LOE and its partners

As a doctoral student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20% of full-time.

Your qualifications

You have graduated at Master’s level in Chemistry, (Applied) Physics, Materials Science, or a related field, or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses in a relevant area. Alternatively, you have gained essentially corresponding knowledge in another way.

We are looking for candidates with a strong interest in interdisciplinary research at the interface of chemistry, physics, materials, and energy technologies. Experience in one or more of the following areas is considered an advantage: fine-tuning machine learning potentials, Hamiltonian learning, molecular dynamics simulations of materials.

The successful candidate has strong problem-solving skills, is able to work effectively in a multidisciplinary and international team and demonstrates excellent communication abilities.

Great emphasis will be placed on personal qualities and suitability.

Your workplace

Join us at the Laboratory of Organic Electronics (LOE) at Linköping University, a world-renowned center for groundbreaking research in bioelectronics, energy devices, printed electronics, and nanooptics using organic materials. Our innovative work focuses on the dynamic coupling of ion and electron movement. At LOE, you’ll be part of a vibrant community of over 150 researchers, including professors, senior and junior scientists, and fellow PhD students. Our collaborative environment is multidisciplinary, fostering creativity and innovation. ( )

You will work within the newly established Computational Materials Science group of Assistant Professor Waldemar Kaiser, part of the Theory & Modelling unit (led by Prof. Igor Zozoulenko). Our focus is on:

Machine-learning accelerated materials simulations

ML-accelerated simulation of ion and charge carrier transport in energy materials

Multiscale modeling of transport in materials

The employment

When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is available

The employment has a duration of four years’ full-time equivalent. You will initially be employed for a period of one year. The employment will subsequently be renewed for periods of maximum duration two years, depending on your progress through the study plan. The employment may be extended up to a maximum of five years, based on the amount of teaching and departmental duties you have carried out. Further extensions can be granted in special circumstances.

This recruitment is connected to the Wallenberg Initiative Materials Science for Sustainability (WISE, ). WISE, funded by the Knut and Alice Wallenberg Foundation, is the largest-ever investment in materials science in Sweden and encompasses major efforts at Sweden’s foremost universities over the course of 12 years. The vision is a sustainable future through materials science. Read more:

All early-stage researchers recruited into the WISE program will be a part of the WISE Research School an ambitious nationwide program of seminars, courses, research visits, and other activities to promote a strong multi-disciplinary and international network between PhD students, postdocs, researchers, and industry.

Starting date

Starting date during Fall 2026.

Salary and employment benefits

The salary of PhD students is determined according to a locally negotiated salary progression. The starting salary for our PhD students is SEK 35,300 per month. This level will be increased during this year's annual salary review in October. As a PhD student, your salary also increases after completing 30% and 60% of your