KTH Royal Institute of Technology, Stockholm, Sweden invites online Application for number of Fully Funded PhD Degree at various Departments. We are providing a list of Fully Funded PhD Programs available at KTH Royal Institute of Technology, Stockholm, Sweden.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in SiC bipolar devices for power electronics
The position will contribute to cutting-edge research on Silicon Carbide (SiC) Bipolar Junction Transistor (BJT) and Insulated Gate Bipolar Transistor (IGBT) devices for next-generation power electronics applications. These devices are crucial for improving energy efficiency, performance, and reliability in industries such as renewable energy, electric vehicles, and industrial automation. The position involves fabrication and characterization of new devices in KTH’s Electrum Laboratory (http://electrumlab.se/kthrise.aspx) with a focus on semiconductor process technology to enhance device performance. The PhD will be part of an internationally recognized SiC research group (https://www.kth.se/ee/ees) and the EU project WBG Pilot line (https://www.wbg-pilot-line.eu).
Deadline : 31.Aug.2026
(02) PhD Degree – Fully Funded
PhD position summary/title: Doctoral students in Networked Systems Security
We invite applications for doctoral student positions with the Networked Systems Security (NSS) lab at EECS/CLS. We are looking for highly motivated individuals to pursue a PhD in security and privacy. The positions involve activities leading to original research and results in peer-reviewed publications. The research topics can relate with any of the NSS group areas (https://www.eecs.kth.se/nss).
The NSS group designs and builds trustworthy networked systems, with a research agenda covering a gamut of security and privacy problems and results that got significant attention by the research community. NSS introduced a new security curriculum at KTH. Candidates with experimental/systems or theoretical profiles and research interests in any aspect of security and privacy are welcome to apply.
Deadline : 23.Aug.2026
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(03) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in geodetic surveying with GNSS
We are looking for a PhD student for the project Efficiency Improvement of Track
Measurements, funded by the Swedish Transport Administration. The main purpose of the project is to design and evaluate GNSS measurement methods that meet the requirements for determining track position. See more detailed project description here.
The PhD student will be placed at the Department of Land Surveying – Property Science and Geodesy and will collaborate with RISE and the Swedish Transport Administration, which are parties to the project. The candidate is expected to have good knowledge in geodesy (GNSS and reference systems), physics (propagation of electromagnetic signals) and mathematics (statistics).
Supervision: Prof. Milan Horemuz and a person at the Swedish Transport Administration is proposed to supervise the doctoral student. Decisions are made on admission
Deadline : 16.Aug.2026
(04) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student (Licentiate) in Engineering Materials Science
Cemented carbide tools are essential to Sweden’s manufacturing, construction, and mining industries due to their exceptional hardness and wear resistance. At the same time, the supply of virgin tungsten (W) and cobalt (Co) is uncertain, and only about 10% of today’s cemented carbide tools are produced from recycled material. Increasing recycling is therefore crucial for reducing energy use, climate impact, and dependence on critical raw materials.
The aim of the PhD project is to contribute to a mechanistic understanding of how recycled raw materials influence the microstructure and performance of cemented carbides in demanding applications, primarily metal cutting but also rock excavation. Recycled raw material often contains impurities which can affect the final properties of the product. The work builds on a pre-study in which real‑time characterization under simulated loading conditions showed strong potential for explaining how impurities and microstructure govern material behaviour.
The project will be carried out within the CHARM project funded by Vinnova and involves close collaboration with leading industrial partners (Sandvik Coromant, Seco Tools, Sandvik Mining) as well as researchers at KTH and Lund University. It is also linked to Vinnova’s competence centre NEXT and European networks such as AIM‑NEXT and RESQTOOL. The work includes development of new characterization methods, analysis of microstructure–property relationships, and knowledge‑based optimization of recycled cemented carbides.
The overall goal is to enable high‑performance tools based on recycled materials, thereby strengthening sustainability, competitiveness, and raw‑material security for Swedish and European industry.
Deadline : 10.Aug.2026
(05) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Sustainable Satellite Networks
Global connectivity relies heavily on terrestrial fiber-optic cables, but their physical vulnerabilities, high installation costs, and sustainability concerns demand a fresh approach. Space-Air-Ground Integrated Networks (SAGIN) offer a solution by fusing space, air, and ground nodes for seamless, ubiquitous coverage. Because light travels roughly 1.5 times faster in space than through fiber cables, modern low-Earth-orbit (LEO) mega-constellations can deliver low-latency, secure, and high-capacity redundancy that rivals traditional ground networks.
In this doctoral project, you will contribute to the evolution of SAGIN, focusing specifically on dual-tier space-ground integrated networks. The goal is to develop the architectural concepts and AI frameworks needed to deliver reliable, low-latency communications across satellite mesh networks. A core hypothesis of this project is that introducing automation and network-aware coordination can overcome the vulnerabilities of manual operations, mitigating the severe impacts of orbital dynamics, space weather, and altitude densification. Methods from satellite communication theory, network optimization, and machine learning will play a vital role. The research will be highly theoretical and algorithmic, focused on the optimization of thousands of dynamic communication nodes.
Deadline : 07.Aug.2026
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(06) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Fluorescence-based Biomolecular Spectroscopy / Imaging
The project will be performed in the Exp Biomolecular Physics group, dept Appl Physics. The research focus of the group is on fluorescence-based ultrasensitive and super-resolution imaging and spectroscopy techniques for molecular and cellular studies, method development as well as applications in fundamental biophysics and towards clinical applications. Within this framework the aim of this project is to develop a new method based on fluorescence blinking, allowing biomedically relevant cellular conditions to be monitored in cells. The project is highly interdisciplinary, and spans both experimental (optics/photonics, spectroscopy/imaging, chemistry, cell and molecular biology), as well as theoretical work (modelling/data acquisition/programming). The project will also include collaboration with biomedical research groups.
Deadline : 31.Jul.2026
(07) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in deep learning for biological systems
The department of Decision and Control Systems (DCS) is currently seeking a doctoral student with a strong background in machine learning, mathematics, and modeling, and an interest in biological systems. The successful candidate will join a project to understand and model cell-cell interactions to disrupt cancer-promoting equilibria. We aim to develop in silico and in vitro models and tools to build and validate digital twins of such interactions, with the objective of steering cellular systems toward healthier states and transforming drug development to reduce trial-and-error and accelerate the translation of discoveries into clinical applications.
DCS conducts fundamental research in machine learning, control systems, and system identification, in partnership with AstraZeneca, SciLifeLab, and the Karolinska Institute. We collaborate with researchers at Caltech, MIT, UC Berkeley, Stanford. This project will be conducted with Professor Avlant Nilsson’s research group, focusing on advancing precision medicine through models of cancer cells.
Deadline : 31.Jul.2026
(08) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Underwater Robotics
The main objective is a proof of concept of multimodality, multi vehicle, localization and change detection in the scenario of collaborating AUVs, that is, the autonomous detection of changes on the seafloor, using multiple vehicles surveying the area and building a detailed 3D model using multimodal sensing over time. We build on the systems and methods developed within SMaRC, but now we will be able to put the parts (SLAM navigation and bathymetric reconstructions, together and add localization, more sensor modalities, multiple vehicles and change detection in a demonstrated simulation of a full resident AUV change detection scenario over time.
Deadline : 12.Jul.2026
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(09) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in brain-like machine intelligence and artificial cognition
This position offers a unique opportunity to develop and advance cognitive brain theories and build computational neural network models to inform the emerging class of brain-inspired AI systems towards brain-like machine intelligence. The successful applicant will capitalise on the vibrant interdisciplinary environment sustained by a strategic collaborations with Karolinska Institute and Stockholm University.
The goal of the project is to develop and simulate large-scale neural network models of the brain’s cognitive function with focus on cortical memory system, and use them to make advances towards brain-like intelligent systems. Special focus is on coupling multiple neural networks to study neural interactions between different cortical regions supporting cognitive function. You are expected to build such large-scale brain plausible network-of-networks models in the continuum between spiking and non-spiking computations, and hence propose novel architectural blueprint for AI agents. You should also be able to evaluate the emerging models given multi-modal data and constraints. The project will involve interdisciplinary efforts across multiple fields including cognitive science, computational neuroscience, machine learning / AI (deep generative modelling) and dynamical systems among others.
Deadline : 10.Jul.2026
(10) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student (licentiate) in Artificial Intelligence for Earth Observation
We are excited to announce a new PhD position in Artificial Intelligence for Earth Observation. This research opportunity will focus on advancing AI-driven Earth Observation (EO) methods for environmental intelligence, with applications including illegal waste monitoring, wildfire emission estimation, and pollution assessment.
The doctoral research will explore cutting-edge artificial intelligence and machine learning approaches for analyzing multi-modal, multi-temporal, and multi-resolution satellite imagery and geospatial data. The project aims to develop innovative models capable of capturing complex spatiotemporal dynamics and supporting a broad range of downstream environmental applications. Particular emphasis will be placed on building robust and scalable AI solutions for environmental monitoring, situational awareness, and sustainable decision-making through EO big data analytics.
If you are passionate about applying artificial intelligence to address environmental challenges and have a strong background in machine learning, computer vision, or remote sensing, we encourage you to apply and join us in shaping the future of AI-driven Earth observation for environmental intelligence.
Deadline : 09.Jul.2026
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About KTH Royal Institute of Technology, Stockholm, Sweden – Official Website
KTH Royal Institute of Technology, abbreviated KTH, is a public research university in Stockholm, Sweden. KTH conducts research and education within engineering and technology, and is Sweden’s largest technical university. Currently, KTH consists of five schools with four campuses in and around Stockholm.
KTH was established in 1827 as Teknologiska Institutet (Institute of Technology), and had its roots in Mekaniska skolan (School of Mechanics) that was established in 1798 in Stockholm. But the origin of KTH dates back to the predecessor to Mekaniska skolan, the Laboratorium Mechanicum, which was established in 1697 by Swedish scientist and innovator Christopher Polhem. Laboratorium Mechanicum combined education technology, a laboratory and an exhibition space for innovations. In 1877 KTH received its current name, Kungliga Tekniska högskolan (KTH Royal Institute of Technology). The King of Sweden Carl XVI Gustaf is the High Protector of KTH.
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