Linkoping University, 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 Linkoping University, Sweden.
Eligible candidate may Apply as soon as possible.
(01) PhD Degree – Fully Funded
PhD position summary/title: PhD Position in Industrial Marketing
The overall aim of the project is to investigate how firms can leverage specialised AI models to develop innovative offerings, business models, and ecosystem collaborations. While much of the public debate on AI focuses on general-purpose models, this project addresses the strategic and organizational implications of AI embedded in specific industrial and commercial solutions.
As a PhD student, you will explore:
- how firms use specialized AI to strengthen their competitive position
- how new offerings and business models emerge
- how value creation and collaboration in ecosystems change when firms develop or adopt AI models
- how firms can retain strategic control in an economy where global platforms often set the rules of the game.
You will work closely with both startups and established firms, in Sweden as well as internationally, and have the opportunity to collaborate with leading researchers at universities around the world. Through the project, you will build unique expertise at the intersection of AI, innovation, and marketing strategy—competencies increasingly sought after in both industry and academia.
The PhD position is part of a research project funded by ELLIIT (Excellence Center at Linköping–Lund in Information Technology) and will be carried out in close collaboration with industry partners. You are expected to participate in international conferences and will have opportunities to spend part of your doctoral studies at well-renowned universities abroad.
Deadline : 16 of April 2026
(02) PhD Degree – Fully Funded
PhD position summary/title: PhD Student in Computational Mathematics
You will be employed at the Department of Mathematics in the Division of Applied Mathematics, https://liu.se/en/organisation/liu/mai/tima. The research group in Computational Mathematics has been one of the most active in Scandinavia over the past decade. Our group is distinguished by its work on fundamental mathematical and computational tools in numerical analysis, computational fluid dynamics, and uncertainty quantification with diverse applications.
Our group maintains active collaborations with other divisions at Linköping University and broader society, e.g., with Saab, FOI, and SMHI. Additionally, there are active international collaborations with universiteis in Germany, Spain, Canada, South Africa, and the USA. This provides an international work environment in which you will carry out teaching and research duties with individuals from all over the world.
Deadline : April 9, 2016
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(03) PhD Degree – Fully Funded
PhD position summary/title: PhD student in Medical Science
As a PhD 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.
As a PhD student, you will work on a project aimed at understanding the consequences of DNA break induction. You will combine advanced genetic engineering approaches with survival assays, fluorescence-based techniques in fixed and live cells, single-cell sequencing, and computational bioinformatics analyses to induce DNA breaks, monitor their formation, and investigate their repair outcomes.
Deadline : 10 Mars 2026
(04) PhD Degree – Fully Funded
PhD position summary/title: PhD student in Medical Science
As a PhD 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.
As a PhD student, you will work on a project aimed at understanding the consequences of telomere deprotection in normal and malignant cells, at both the cellular and molecular levels. At the cellular level, you will investigate the fate of cells experiencing telomere dysfunction. At the molecular level, your work will explore key aspects of telomere dysfunction, including DNA end processing, chromatin dynamics, and repair outcomes. The research will be experimental character, including cell culture, genetic manipulations, analysis of genomic rearrangements, telomere assays, and RNA sequencing. The activities include literature review, lab working and computational bioinformatics analysis.
Deadline : 10 Mars 2026
(05) PhD Degree – Fully Funded
PhD position summary/title: PhD in Applied Physics
In this project, you will build an experimental and computational platform based on 3D-printed, brain-mimetic tissue models with tunable transport properties, where interface transport can be measured and predicted. The platform will measure and model how substances spread, are taken up, and are cleared over time and space, including nutrients, drugs, neuromodulators, and electrode precursors. You will investigate selected materials, device designs, and operational modes for these bioelectronic implants. You will also develop and validate finite element models (COMSOL Multiphysics) to support the experimental work. The work is experimentally driven (approximately 70/30 wet lab to modeling) and will include:
- Design and fabrication of 3D-printed brain tissue models with tunable transport properties
- Development of experimental methods to investigate spatiotemporal transport phenomena across the implant-tissue interface
- 3D cell cultures and cell-based evaluation of transport-driven biological responses
- Multiphysics modeling using COMSOL Multiphysics, validated against experimental data
Deadline : March 9, 2026
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(06) PhD Degree – Fully Funded
PhD position summary/title: PhD student in Statistics
As a PhD 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 per cent of full-time.
The research projects for the advertised position will be in the area of branching stochastic processes for phylogenetic comparative methods.
This is primarily focused on fundamental research on the development of new inference methods and algorithms for wide classes of stochastic models. However, research will be conducted in collaboration with biologically oriented researches allowing for testing and applying the methods on real data.
Deadline : March 3, 2026
(07) PhD Degree – Fully Funded
PhD position summary/title: PhD student in Bayesian Computational Mathematics
A central challenge in computational mathematics, as well as machine learning, is ensuring reliability and trustworthiness. This is especially crucial in applications such as medical diagnosis, weather forecasting, and aircraft design. To improve the reliability and trustworthiness of mathematical models and machine learning tools (e.g., neural networks) in a meaningful way, we need innovative, scalable methodologies that efficiently and accurately capture, represent, and reason about uncertainties within principled frameworks.
You will join the research group of Jan Glaubitz and develop your own research agenda in the context of the group’s research at the intersection of inverse problems, Bayesian learning, and uncertainty quantification. The specific project will be tailored to your expertise and interests; examples include:
- Efficient inference techniques for high-dimensional Bayesian inverse problems for image reconstruction and chemical reaction neural networks with sparsity-promoting (and edge-preserving) priors, including diffusion-based approaches.
- Neural solvers for hyperbolic conservation laws and other time-dependent partial differential equations relevant to computational fluid dynamics. These efforts might include Bayesian physics-informed neural networks and neural operators.
- Bayesian neural networks for approximating piecewise smooth functions and solutions (in imaging and computational fluid dynamics) with uncertainty quantification.
Deadline : 2 March, 2026.
(08) PhD Degree – Fully Funded
PhD position summary/title: PhD Student in Automatic Control
You will work on a project on data driven control. In recent years, data-driven control in high dimensions has penetrated many new application areas. Examples include control of autonomous vehicles based on video data, simulation-based prediction of turbulent flows and precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is hampered when the number of time samples is small compared to state dimensions, while latency and stability remain central concerns. As a result, learning-based feedback in high dimensions is still carried out without a solid theoretical foundation. This leads to unpredictable behavior, which is a major bottleneck for efficient and resilient control of complex systems in engineering and medicine. Your research will bridge this gap, and it will be carried out in collaboration with Professor Anders Rantzer at the Department of Automatic Control at Lund University, and within ELLIIT.
As a PhD 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 per cent of full-time.
Deadline : February 27, 2026
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(09) PhD Degree – Fully Funded
PhD position summary/title: PhD Student in Automatic Control with focus on sensor informatics
This PhD project is part of a close collaboration between Linköping University and Lund University within the ELLIIT programme (https://elliit.se/) and aims to develop the next generation of intelligent sensor systems capable of providing reliable situational awareness in complex and dynamic environments. The research is driven by applications where current technology is insufficient, such as large-scale biodiversity monitoring in natural environments, smart agricultural and ecosystem applications within AgTech (https://agtechsweden.com/), search-and-rescue operations in challenging terrain, and intelligent surveillance for societal security. By combining machine learning with model-based methods, the project enables systems that can detect, distinguish, and track multiple simultaneous events or objects using sensor information from, for example, radio, audio, and vibration signals, even under uncertain and disturbed conditions. The goal is to develop robust and scalable solutions that can form the basis for future technological breakthroughs in areas ranging from environmental monitoring and emergency response to security and biodiversity conservation.
Deadline : February 27, 2026.
(10) PhD Degree – Fully Funded
PhD position summary/title: PhD Student in Automatic Control with focus on sensor fusion for distributed situational awareness
The advertised positions will be within the Competence Center SEDDIT (Sensor Informatics and Decision-Making for the Digital Transformation). Read more about the Competence Center here: https://liu.se/forskning/seddit.
The focus of this specific PhD project is to explore methods for distributed state estimation in large and heterogeneous sensor networks, with particular emphasis on statistical model‑based approaches. As sensor systems scale up to vehicle fleets, drone swarms, and large‑scale environmental monitoring, traditional centralized solutions quickly become insufficient due to communication constraints, computational demands, and sensitivity to failures in the central node. The work includes developing scalable methods for information compression, robust detection of faulty or malicious nodes, and principles for handling uncertain or varying sensor quality. The goal is to enable efficient, robust, and high‑quality situational awareness in complex and dynamic networks, thereby laying the foundation for future autonomous and data‑driven systems.
Deadline : February 27, 2026.
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(11) PhD Degree – Fully Funded
PhD position summary/title: PhD Student in Automatic Control with focus on sensor fusion for localization
This PhD position is part of the ELLIIT research program (https://elliit.se) and focuses on enabling reliable robot situational awareness in challenging and unpredictable environments. The project is grounded in statistical, model‑based methods that combine multi‑object tracking with simultaneous localization and mapping (SLAM). By leveraging semantic information, the aim is to improve data association, handle multiple hypotheses efficiently, and build consistent maps while simultaneously tracking dynamic objects. The overarching goal is to develop robust and scalable methods that enhance a robot’s understanding of its surroundings, with the intention of demonstrating the results in a simplified lab environment. The student will work closely with a twin PhD project at Lund University, which focuses on learning‑based generation of the type of semantic information used in this work.
As a PhD 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 per cent of full-time.
Deadline :February 27, 2026.
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(12) PhD Degree – Fully Funded
PhD position summary/title: PhD Student in Automatic Control with focus on control allocation for future stealth aircraft
In this project, you will work and collaborate within an international research project involving several of the world’s leading aerospace organizations. It is a subproject of a NATO-wide initiative where participating organizations can test new control algorithms on sub-scale 3D-printed aircraft, developed and provided by IEI at Linköping University. This PhD project, funded by Saab, focuses on developing advanced optimization-based control algorithms for control allocation for next-generation fighter aircraft. Control allocation is of particular interest when a vehicle has multiple ways of being controlled (redundant actuators), where each method has its own advantages and disadvantages regarding factors such as radar signature and fuel consumption. Specifically, the challenges posed by stealth aircraft will be addressed, where a large number of cooperating control surfaces and/or thrust vectoring control (TVC) may be required to guarantee the platform’s safety and controllability. A key component of the planned research is the state-of-the-art QP solver daqp for embedded optimization, developed by the research group.
Deadline : February 27, 2026
(13) PhD Degree – Fully Funded
PhD position summary/title: PhD Student in Automatic Control for Adaptive Hearing Aids
We are seeking a PhD student in automatic control for a research project on the development of next-generation hearing aids. The project builds on previous research on modeling human hearing and aims to develop adaptive hearing aids that can adjust to the user’s cognitive state.
The project investigates how audio signals and brain activity, measured using electroencephalography (EEG), can be used to estimate both how well a sound is perceived and how cognitively demanding a listening situation is. These measures are then incorporated into feedback control systems to automatically adjust the functionality of a hearing aid, with the goal of enabling the user to clearly perceive a desired sound source without excessive listening effort.
This is an interdisciplinary project conducted within the ELLIIT research environment (www.elliit.se). The work is carried out in close collaboration with researchers in signal processing at Lund University, as well as researchers in hearing and neuroscience at Eriksholm Research Centre, which is part of the world-leading hearing aid manufacturer Oticon.
Deadline : February 27, 2026.
(14) PhD Degree – Fully Funded
PhD position summary/title: PhD Student in Automatic Control with focus on optimization under uncertainty
You will work within a project focused on optimization, planning, and decision-making in control systems involving uncertainties. Determining how to account for these uncertainties leads to research questions spanning from data collection and estimation to model representations and optimization algorithms. In the field of automatic control, one must also consider stability and performance under feedback control. This research is conducted within the framework of the SEDDIT competence center.
As a PhD 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 per cent of full-time.
Deadline : February 27, 2026.
(15) PhD Degree – Fully Funded
PhD position summary/title: PhD Student in Automatic Control with focus on learning robotics
We are currently looking for a PhD student to conduct research on the intersection of robotics and control theory.
Project description: This PhD project aims to develop learning‑based methods that combine expert demonstrations with experiential reinforcement learning to enable robust, data‑efficient skill acquisition. Expert data offers fast, safe, and reliable initial learning, while reinforcement learning supports systematic exploration and adaptation to new conditions. By integrating these two paradigms, the project seeks to create generalizable strategies for mobile manipulation that perform effectively across diverse real‑world scenarios. The following research directions will be followed:
- Q1: How can an agent leverage multi‑modal expert demonstrations (e.g., vision, force, proprioception) to acquire coherent and transferable mobile manipulation skills?
- Q2: How can an agent use experiential learning to control redundant degrees of freedom and handle task variations beyond those demonstrated?
The research is carried out within the ELLIIT project “Learning Robot Control from Expert Demonstrations and Self-Experience” (https://elliit.se/).
Deadline : February 27, 2026
(16) PhD Degree – Fully Funded
PhD position summary/title: PhD student in Visualization and Media Technology with a focus on visual learning and communication
The advertised position is part of a Marcus and Amalia Wallenberg (MAW) foundation funded project that investigates the possibilities and implications of AI-enabled conversational guides on visitors’ learning and experiences in public educational environments, such as the Visualization Center in Norrköping. The goals of the project are to identify AI-guide characteristics, investigate interactions between AI-guides, pedagogues and visitors, and explore the combination of visuo-verbal interactions for enhancing engagement and learning with interactive exhibits in public spaces. The PhD student will collaborate closely with visualization researchers, AI-specialists, research engineers, educational scientists, and pedagogues, across Linköping University, the Visualization Center, and Umeå University to study the impact of emerging AI-driven educational technology on learning in public spaces.
The PhD student is expected to produce research outputs relevant to the fields of visualization, visual learning and communication, and educational science. These outputs should include publications at international conferences, workshops, and journals. As this research is highly collaborative, the PhD student should thrive within and be passionate about contributing to a vibrant interdisciplinary research environment.
As a doctoral student, you devote most of your time to doctoral studies and the research project of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20% of full-time. Alternatively, if you have a strong software engineering background, you will have the opportunity to fill this 20% effort with additional research engineering work.
Deadline :25th of February 2026.
About Linkoping University, Sweden –Official Website
Linköping University is a public university in Linköping, Sweden. Linköping University was granted full university status in 1975 and is now one of Sweden’s larger academic institutions. Education, research and PhD training are the mission of four faculties: Arts and Sciences, Educational Sciences, Medicine and Health Sciences, and the Institute of Technology. In order to facilitate interdisciplinary work, there are 12 large departments combining knowledge from several disciplines and often belonging under more than one faculty. Linköping University emphasises dialogue with the surrounding business sphere and the community at large, both in terms of research and education. In 2018, Linköping University was home to 32,000 students and 4,000 employees.
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