Postdoctoral Fellowship (20) at KTH Royal Institute of Technology, Stockholm, Sweden

We are looking for a postdoctoral fellow to develop and improve models and codes for assessment of the liquid source term during severe accident (SA) of LWR systems. In particular, research will include assessment of the characteristics of the containment water pool by system code, thermodynamic and kinetic aspects of Cs and Sr chemistry including model development and its implementation to the system codes.  This project is contributing to the larger EU project SOCRATES which addresses the critical gaps in understanding of the liquid source term during SA and offers innovative solutions to mitigate and monitor the release of radionuclides into the environment.

The goal of this position is to conduct independent research and develop theories and methodologies that help in improving the reliability and trustworthiness of large-scale machine learning models (e.g., LLMs) in a meaningful way. You will be joining the research group of Martin Trapp and develop your own research agenda in the context of the group’s research. A particular focus of the group is to develop and utilise theories from tractable models (probabilistic circuits) and Bayesian statistics to tackle the reliability of machine learning models, touching topics such as uncertainty quantification in large-scale models, exact and approximate inference, and neurosymbolics. See Martin Trapp’s website for details. The candidate is expected to augment the research expertise of the group through her/his own experience and to conduct research in close collaboration with the group. You will develop theoretical and methodological work that will be released as open-source libraries and publish your work at top-tier machine learning venues (NeurIPS, ICML, ICLR, UAI, AISTATS). Moreover, you will have the opportunity to collaborate with researchers working on machine learning at KTH and collaborate with international experts through the group’s network.

The Division of Highway and Railway Engineering is seeking a motivated and collaborative postdoctoral researcher for a project on developing machine learning tools for pavement management. The project is conducted in collaboration with the Swedish Transport Administration and partners from the road industry.

The project aims to create data-driven decision support tools for predicting pavement performance and planning maintenance and reinforcement. It will build on extensive pavement performance datasets and apply advanced machine learning and statistical methods to generate predictions and assess the effectiveness of different maintenance and reinforcement strategies. The postdoc will lead work on extracting and analyzing pavement condition and traffic data, integrating them with climate and environmental datasets, and developing validated predictive models of pavement deterioration.

The position is research-focused, with opportunities to strengthen independence and build qualifications for future academic or industry careers. Teaching at various academic levels may also be included. The work will take place in a multidisciplinary environment combining expertise in pavement engineering, mechanics of pavement materials and structures, and machine learning. The role offers opportunities to contribute to high-impact publications and to practical decision support tools for the road engineering community.

1 postdoctoral position is offered within the Random Matrices and Random Geometry research group in the KTH mathematics department.

The project will take place under the supervision Prof. Fredrik Viklund and will involve the study of one or more of the following areas: Coulomb gases  and related areas, 2D random conformal geometry (SLE theory, lattice models, gaussian fields, etc), conformal field theory, gauge theories, the Loewner energy, or other topics consistent with the research interests of the supervisor. 

Driven by the urgent challenges of climate change and energy security, energy systems are undergoing a paradigm shift toward a fully renewable and power-electronic-dominated future. This project aims to develop smart converters for future power converter dominated grids.

The research focuses on developing modeling/simulation of power converter dominated grids, stability analysis, AI driven coordination (e.g., safe DRL).

The recruited researcher will join the Division of Electric Power and Energy Systems at KTH Royal Institute of Technology, working closely with world-leading power electronic groups in University of Padova, Aalborg University, Chalmers University of Technology , and with a set of industrial partners, i.e., two units of Hitachi Energy and Energiforsk, the system operators Terna and Svenska kraftnät, Volvo Energy, and Norlys Energy Trading.

We invite applications for one Postdoctoral Researcher position in the Communication Systems (COS) Division at KTH led by Prof. Emil Björnson. The position is part of the international research project 6GSTAR, which involves KTH, Northeastern University (Boston, MA, USA), and the Singapore University of Technology and Design (SUTD, Singapore). The postdoc will become part of the TERANET@KTH research lab.

The team will also work in close collaboration with other academic and industrial partners (e.g., Ericsson) in Sweden and abroad, as a part of large-scale European research initiatives by KTH, including DICE-6G, SMART-6GSAT, and SweWIN.

The postdoc will contribute to the design and development of next-generation of Low Earth Orbit (LEO) satellite communication systems utilizing extremely-high-rate sub-terahertz (100 GHz – 300 GHz) spectrum for mobile wireless links. The postdoc will also work closely with international collaborators, through (among other possibilities) research visits to other research labs on sub-THz and LEO satellite networks in Europe, USA, and/or Singapore.

The position offers excellent opportunities for high-impact publications, contributions to demonstrators and standardization, and professional development in academia and industry.

The Nuclear Science and Engineering (NSE) Division seeks an ambitious, motivated, structured, and collaborative postdoc to join the nuclear fuel materials team to study the thermal stability and pellet-cladding mechanical and chemical interaction of burnup simulated doped UO2 fuel (ADOPTTM SIMFUEL). The project is supported by the Swedish Radiation Safety Authority (https://www.stralsakerhetsmyndigheten.se/) and in collaboration with Westinghouse and Chalmers University of Technology. You will lead research efforts using experimental and computational methods to evaluate the effect of fission products on the thermal and mechanical properties and on the pellet cladding mechanical and chemical interactions (PCMI and PCCI) of Cr2O3 and Al2O3 doped UO2.

The project is part of the EU Horizon project “ODDYSEV – Optimised DYnamics of high voltage powertrains: developing Sustainable Systems for Electric Vehicles”.

The goal is to design a high-voltage motor using tools for shape and topology optimization, rather than parametric optimization algorithms. The optimization may also leverage the capabilities of AI tools to deliver a solution with wide speed operation, achieving peak efficiency over 95%. The optimization will include system-level constraints to reflect the complexity of a powertrain for automotive purposes.

ODYSSEV is a collaboration between 14 universities and companies, enabling a cross-boundary networking and knowledge exchange that will result in solid solutions for the electromobility market.

Conduct research in algebraic combinatorics under the supervision of Professor Petter Brändén. The position is 80% research and 20% teaching.

Urban mobility is changing rapidly due to new business models, and upcoming technological advancements like connected and automated mobility.

The Division of Transport and Systems Analysis at KTH is seeking a highly qualified candidate for a postdoctoral research position in Transportation Policy. The successful candidate will conduct research on policies related to on-demand responsive mobility, with the overarching goals of reducing transport inequalities, enhancing accessibility, and improving social welfare. The postdoc will employ methodologies such as activity-based agent-based modeling, social welfare theory, and distributional analysis. Case studies will be developed in collaboration with local transport agencies and mobility providers.

The appointee will work on an ambitious project aimed at helping cities to reduce their greenhouse gas emissions and achieve climate neutrality. The project will combine world-leading research on climate action, the use of AI in urban planning, and nature-based solutions (NBS) to create a tool which supports cities in implementing effective climate action strategies through spatial planning. The appointee will be responsible for leading the modelling work on this project and coordinating the research and practical aspects of the project from both the involved Swedish cities and international research partners.

It is essential for the applicant to have solid theoretical and applied background in sustainable urban and regional planning, decision support systems, nature-based solutions, and carbon neutral cities.

The candidate is expected to produce high-quality scientific papers, suitable for publication in high profile journals and presentations at national and international conferences, and contribute for external funding proposals. In addition to this, the candidate will need to interact with various Swedish planning authorities for project coordination and communication.

The Departments of Engineering Mechanics and Chemical Engineering at KTH Royal Institute of Technology are seeking a highly motivated postdoctoral researcher to join a new interdisciplinary project funded by Digital Futures, titled “AI for Clean Energy Conversion: Learning Multiscale Dynamics in Fuel Cell Systems”.

The project aims to develop a multiscale modeling framework that combines computational fluid dynamics (CFD), electrochemical experiments, and machine learning (ML) to understand and predict multiscale transport phenomena in fuel cell systems. In particular, the postdoc will bridge pore-scale simulations and macroscale performance models using advanced operator learning and physics-informed AI techniques, leveraging high-resolution X-ray imaging data and high-performance computing (HPC) resources.

The position offers a unique opportunity to work at the interface of AI, computational physics, and electrochemistry, within two vibrant research environments (FLOW and Applied Electrochemistry) and to contribute to the development of next-generation tools for sustainable energy conversion.

Centre X is seeking a highly motivated and specialized postdoctoral researcher with a strong background in surface texture control and characterization for advanced manufacturing systems, specifically precision machining. This role is a key part of the industry-driven collaborative initiative, Centre X (Advanced Manufacturing Solutions for Next Generation Powertrain), a joint effort by KTH Royal Institute of Technology, Chalmers University of Technology, Scania CV AB, and AB Volvo.

The primary objective of this position is to conduct in-depth, experimental and theoretical research on the control and characterization of surface integrity in high-performance machining processes. The successful candidate will focus on the fundamental understanding and application of ISO 25178, ISO 21920, ISO 16610 series, and other relevant 2D and 3D surface roughness/waviness parameters, their interdependencies, and their direct impact on component performance and reliability in powertrain applications. This includes linking machining parameters—such as tool geometry, cutting speed, feed rate, and lubrication—to resulting surface characteristics. The role requires deep knowledge of advanced machining processes, including hard turning, high-speed milling, and gear manufacturing, with a strong emphasis on understanding how process-induced surface features affect functional performance, such as fatigue and wear.

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: Postdoc in Socially Interactive Virtual Characters

Deadline : 15.Nov.2025

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Driven by the urgent challenges of climate change and energy security, energy systems are undergoing a paradigm shift toward a fully renewable and power-electronic-dominated future. This project aims to develop innovative solutions for the seamless integration and reliable operation of large-scale converter-interfaced renewable energy systems by leveraging AI-driven techniques.

The research focuses on developing advanced optimization and control strategies (e.g., deep reinforcement learning) for large-scale sustainable grids, to enhance overall system stability, flexibility, and resilience.

The project is funded by Swedish Energy Agency.  The recruited researcher will join the Division of Electric Power and Energy Systems at KTH Royal Institute of Technology, collaborating closely with Swedish DSOs.

We look for up to three postdocs to join TECoSA (The Vinnova Center for Trustworthy Edge Computing Systems and Applications). The TECoSA research center is a long-term initiative based at KTH in Stockholm, currently operating with 14 large and smaller industrial partners.

The job will entail:

• Research in one of the following prioritized tracks and tight collaboration with the other two tracks:
• Trustworthiness Assurance – Focus on certification for cyber-physical systems interacting with smart digital infrastructure, such as robotics, transportation, and telecom. Research areas include trustworthiness metrics, system architectures, assurance frameworks, efficient verification and validation, explainability of AI, and managing residual risk.
• Edge AI – Investigate the integration of AI and edge computing, particularly in network optimization, distributed decision-making, and large-scale foundation models. We seek candidates interested in theoretical analysis and optimization of Edge AI to develop robust and secure ecosystems.
• Industrial Edge Applications – Explore future networked robotics, human-in-the-loop systems, and connected transportation. Work with TECoSA’s 5G edge computing testbeds to expand capabilities toward 6G, O-RAN, and AI-RAN while collaborating on application experimentation.
• Collaboration with TECoSA researchers and industrial partners.
• Work on the TECoSA indoor or outdoor testbed.