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 students in Theoretical Chemistry
In the interfacial layers between solid and liquid materials, several of the most important processes occur in both living and artificial systems. The properties of molecules can drastically change when they are in interfacial layers, which can be exploited for, among other things, detection and efficient catalysis. Often, models with thousands of atoms are required to describe this type of system. At the same time, many processes of interest depend on a quantum chemical description, such as chemical reactions or the interaction between molecules and light. We are interested in two specific systems: molecules on the surface of large proteins linked to Alzheimer’s disease, and molecular catalysts on the surface of electrodes, for example, in the production of hydrogen. The size of these systems is far beyond what conventional quantum chemical software can handle. In collaboration between the Department of Theoretical Chemistry and Biology and the supercomputer center PDC at KTH, a new quantum chemical software has been developed that is tailored for modern supercomputers. This enables studies of systems at least 10 times larger, allowing us, for the first time, to approach the processes described above with a full quantum chemical description. The doctoral positions involve studying the systems, testing the software on national and European supercomputers, and developing simpler methods necessary to describe the systems in question. In both projects, collaboration with experimental research groups will occur regularly.
Deadline : 15.Nov.2023
(02) PhD Degree – Fully Funded
PhD position summary/title: PhD in Computer Science with a focus on High-performance Parallel Computing
We invite highly motivated candidates to apply for one full-time doctoral student position in Computer Science (with a specialization in high-performance computing) at ScaLab at the KTH main campus in downtown Stockholm. ScaLab focuses on designing and optimizing algorithms, systems software, and architecture to improve the scalability of large-scale parallel computing. The doctoral students will work in a diversified research group, closely interacting with leading research groups in Europe and USA. Candidates with experience in Linux kernel development, architecture simulators, k8s, or large-scale HPC applications are welcome to apply. The position will work on the co-design for the computing continuum from high-performance computing to cloud. The research targets heterogeneous computing systems, including multi-core processors, GPUs and DPU accelerators, and HBM and NVM memories. The doctoral students will research novel system solutions to be integrated into Kubernetes plugins, MPI, runtimes, and libraries to improve the scalability and efficiency of applications on such computing platforms. The student is expected to publish research outcomes with open access to peer-reviewed conferences and journals. The doctoral student will also be able to develop project management skills for multi-nation projects.
Deadline : 02.Nov.2023
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(03) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in high-speed datacenter networking
Today’s cloud and edge datacenters struggle to keep the pace of multi-100Gbps network interface card. A CPU transmitting 40Gbps of traffic consumes as much as 70% of its cycles, which cannot be used to run any applications. The recent rise of programmable high-speed hardware devices including P4 switches and SmartNICs have opened the doors to massive potential performance gains by offloading networking stacks from CPUs to hardware. Yet, reaping the benefits of such devices is today a largely unsolved problems. For example, multi-terabit per second network devices drop packets depending on specific time patterns. In this project, we plan to build radically new frameworks for controlling network and their performance in a programmatic manner. This research aims to publish work at the top venues in network systems (i.e., SIGCOMM and NSDI) and collaborate with industrial partners (e.g., Intel, Nvidia, Ericsson, Saab). In this project, you will have great possibilities to make impact in society and industry.
Deadline : 31.Oct.2023
(04) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in nonlinear data-driven control
Autonomous systems, such as self-driving cars, rely on advanced control algorithms to make decisions and navigate complex environments, such as Model Predictive Control (MPC). However, traditional MPC methods are limited by the accuracy and availability of models. With the increasing availability of sensor data, data-driven MPC has emerged as a promising solution but most current approaches are limited to linear systems. This project aims at breaking the barriers to nonlinear data-driven MPC, by developing tools for nonlinear state estimation (based on differential-geometric methods), novel neural network architectures for mapping past data into optimal controls and efficient experiment design techniques for data collection.
Deadline : 27.Oct.2023
(05) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Nuclear Power Safety Analysis
The Division of Nuclear Power Safety conducts research on accident phenomena of risk importance to existing and future nuclear reactors, and performs safety analysis for nuclear power plants, including design basis accident analysis and severe accident analysis. The research projects involve extensive international cooperation. We are looking for a doctoral student to carry out frontier research on modeling of accident phenomena in nuclear reactors and perform safety analysis for nuclear power plants. The successful candidate is expected to (i) perform safety analyses of nuclear power plants using U.S. NRC codes; (ii) quantify uncertainties of the analyses; and (iii) extend the codes’ capabilities for simulations of accident phenomena important to Swedish nuclear reactors.
Deadline : 20.Oct.2023
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(06) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Nuclear Power Safety
The Division of Nuclear Power Safety conducts research on reactor accident phenomena of risk-importance and performs safety analysis for nuclear power plants. The NPS research projects involve extensive international collaboration. The position relates to the project entitled “Computational Thermodynamics in Severe Accident Analysis” supported by Swedish Radiation Safety Authority (SSM www.stralsakerhetsmyndigheten.se/) within the call of 2023 “Severe accidents and accident chemistry” to strengthen the knowledge base and maintain national competence in the field of radiation safety in nuclear technology and engineering . We are looking for a doctoral student, who has MS degree in nuclear engineering, nuclear power safety or similar specializations, to carry out frontier research on the safety of light water reactor (LWR) with a focus on severe accident (SA) research and management with application of novel thermodynamic approach. Experience in SA research and codes, such as MELCOR, but also in thermodynamics (TD) and TD databases, such as NUCLEA, will be considered as an advantage.
Deadline :19.Oct.2023
(07) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Numerical simulations in fluid mechanics
This project is part of LUBFLOW, which has the objective to develop a fundamental understanding of lubricant-infused surfaces in fluid flows, which could have significant implications for various technological applications. We are now seeking a PhD student in computational fluid mechanics. A lubricant-infused surface (LIS) is a structured surface infused with a viscous liquid layer. These slippery surfaces are partially inspired by the carnivorous Nepenthes pitcher plant. LISs have shown great promise for reducing fluid friction, preventing biofouling and increasing heat transfer in fluid flows. However, the behaviour of LISs in realistic flow environments is very difficult to predict. LUBFLOW will therefore investigate LISs in fluid flows that include turbulence, surfactants and bacteria. This could lead to better control of fluid flows and broad technological advancements.
Deadline :12.Oct.2023
(08) PhD Degree – Fully Funded
PhD position summary/title: PhD in generative AI and expressive speech synthesis for social inclusion
The goal is to implement and evaluate the usefulness of a generative AI and expressive speech synthesis in Augmentative Communication Technology for individuals with communication disabilities. The project will use the KTH conversational text-to-speech system with context-adaptive expressive control (https://www.speech.kth.se/tts-demos/), As the AI voice system is designed for users who input text using gaze trackers the project also involves using Large Language models to speed up the text input given the previous context. The research takes place at the division of speech, music and hearing, in an interdisciplinary group focusing on modeling and understanding human communication, including speech, language, and gesture using computational and AI-based methods.
Deadline : 10.Oct.2023
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(09) PhD Degree – Fully Funded
PhD position summary/title: Doctoral students in theoretical condensed matter physics
Quantum materials have stimulated a host of new ideas based on unconventional correlated, entangled, and topological orders. Correlations, entanglement, novel dynamic orders determine the properties of quantum materials and naturally reveal themselves in the time domain. We seek a qualified PhD student to work on Dynamical Quantum Matter with particular focus on dynamic superconducting states, odd-frequency superconductivity, dynamic multiferroicity and Dirac materials. Work will be done in the context of the ERC Synergy project on hidden, entangled and resonating orders (HERO) Machine learning and data informatics Recent growth of computational power and high demand for prediction of materials opens new pathways to search, classify and predict materials using materials informatics. This approach places the main effort on performing high-throughput computing combined with data mining and machine learning tools. Applications of this data-driven approach are wide-ranging and cover the search for quantum materials with special electrical, optical and magnetic properties. Successful candidate(s) are expected to bridge the analytic and ab initio calculations in the framework of density functional theory within the field of quantum materials, including van der Waals and Dirac materials, topological materials, superconductivity, photovoltaics and multiferroics. The project is closely tied to the development of the open-access Organic Materials Database (OMDB) https://omdb.mathub.io at Nordita.
Deadline : 06.Oct.2023
(10) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student (licentiate) in Public Transport Network Design
In order for Sweden to achieve its transport policy sustainability goals, a large number of different solutions are required, where competitive public transport is a fundamental component. An efficient line network is important for two reasons: firstly from a socio-economic point of view, as savings in the form of faster journey times mean profits for the individual, and secondly from an economic point of view in the form of savings for authorities. In practice, the development of line networks takes place with a qualitative, artisanal know-how. At the same time, digital developments have enabled new tools to understand passenger movements (e.g., data from digital ticketing systems) and more computing power to perform complex calculations, creating the potential to use algorithms to create more efficient line networks. We are now looking for a PhD student who, in collaboration with Region Stockholm and Nobina Sweden, wants to contribute to the development of practically useful algorithms and processes for designing line networks for public transport. The research is intended to include knowledge gathering through literature search and dialogue, further development of algorithms and investigation of new data sources, development of tools for communication of results, and investigation of potential for commercialization.
Deadline : 06.Oct.2023
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(11) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in metabolic engineering of Saccharomyces cerevisiae for anaerobic production
The overall purpose of this project is to design, test and build new anaerobic pathways for low-molecular-weight microbial products that hitherto can only be made aerobically. Microbial metabolic pathways for anaerobic production of a desired chemical provide by definition the most efficient stoichiometric biotechnological option when thermodynamically feasible. Starting with proof-of-principle anaerobic production with yeast, general pathway-design strategies will be derived that can be applied to economically efficient and sustainable production of chemicals. The project will apply state-of-the-art molecular biology techniques, genomics and proteomics, enzyme-constrained genome scale models, combined with laboratory evolution and quantitative physiology in bioreactors. The PhD student will communicate scientific progress within the team at KTH, as well as through oral presentations, scientific publications and through information for a general audience. In addition to the research, the PhD student will contribute to (co-)Supervision of MSc students and teaching and supervision in lab courses on Cultivation Technology and Bioprocess Design.
Deadline : 05.Oct.2023
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(12) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Neuronic engineering
The Division of Neuronic Engineering at KTH focuses on research on neck and head biomechanics. Finite Element (FE) models of the human neck and head have been developed to study the neck and head kinematics as well as stresses of various kinds. This project aims to improve the prediction of brain injuries for these FE models through accident reconstructions. The project uses accident reconstructions as a tool for understanding injury mechanisms, developing the FE model and developing prevention systems to reduce the number of head injuries. Therefore, expertise in accident reconstruction, biomechanics and finite element simulations are needed. Applicants should have good knowledge of mechanics and understanding of motion analysis or biomechanics. Furthermore, applicants should have basic studies at the MSc level in medical engineering, biomechanics, engineering physics, mechanical engineering, or the like.
Deadline : 05.Oct.2023
(13) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in generative AI for sign language
This PhD project aims to create cutting-edge models for converting written language to sign language through 3D signing avatars. Using generative AI methods, the research combines large language models with deep probabilistic motion generation in 3D animation. This ambitious project builds on our recent pioneering work in diffusion-based motion generation . Automatic sign language technologies contribute to increased inclusion and have high societal importance, yet the problem is under-studied compared to written and spoken language. The research takes place at the division of speech, music and hearing, in an interdisciplinary group focusing on modeling and understanding human communication, including speech, language, and gesture using computational and AI-based methods. This is a highly active and dynamic research field spanning machine learning, natural language processing, signal processing, computer vision, computer graphics and perceptual psychology. You will be working alongside other PhD students and faculty working on e.g., natural speech- and gesture generation, dialog systems and social robotics, and more.
Deadline : 02.Oct.2023
(14) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in space physics
The goal of the project is to advance our understanding of solar wind formation and energization processes. The work is based on observations of the solar wind by the NASA Parker Solar Probe spacecraft launched 2018 and according to NASA being the first-ever mission to “touch” the Sun. Parker Solar Probe allows for the first time sampling regions where significant solar wind acceleration is ongoing locally. The solar wind formation is a very dynamic process and the project plans to quantify the relative role played in it by localized dynamic structures such as switchbacks, current sheets, and flux ropes forming at close distances to the Sun. The project focuses on the regions around the critical Alfvén surface. In this important region, the solar wind goes from being sub-Alfvénic at smaller distances to being super-Alfvénic at larger distances. Scientists and doctoral students at Space and Plasma Physics Division play an active role in many international and national space projects, including the building of instruments and analysis of data. At the division, we also do science within basic plasma physics, fusion research and industrial plasma physics applications.
Deadline : 02.Oct.2023
(15) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Autonomous Anti-Drone Drones
Recently, an increasing number of illegal drone missions have been flown over sensitive infrastructure in Sweden, such as nuclear power plants and airports. These missions are hard to stop or prevent, since drones are fast, small and can land anywhere. This project aims to develop solutions and algorithms for a system of anti-drone drones (ADDs) that are able to stop such intrusions, by detecting, localizing, following and when needed physically de-mobilizing the intruding drones. These problems will be addressed using tools from areas such as control theory, reinforcement learning, game theory, AI and multi-agent coordination.
Deadline : 02.Oct.2023
(16) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in High-Performance Computing using FPGAs for use in Space
In the not-so-far future, space missions will reach distant and unexplored Solar system regions. These space missions will rely on advanced space probes that act as experimental laboratories and continuously collect data and measurements, thus producing a large volume of data that must be analyzed in real-time before transmission to the ground, which is challenging. The Automatics in SpAce exPloration (ASAP) is an upcoming EU project that tackles said challenge by the development of intelligent algorithms for automatic operation in future space missions. Among the technologies that ASAP will rely on are Field-Programmable Gate Arrays (FPGAs). We are now seeking a Ph.D. student who will work on the ASAP project with a particular focus on creating specialized accelerators using FPGAs for future potential use aboard spacecraft. This project is funded by the European Commission, and the Ph.D. student will work on several aspects, including reconfigurable computing and AI/ML/brain-inspired computing. The student is expected to disseminate research results in top-tier international journals and conferences. In addition, the Ph.D. student will actively participate in department and group activities (such as seminars, courses, and conferences) as well as participate in teaching.
Deadline : 02.Oct.2023
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(17) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in formal methods for robotics
We look for a doctoral student to join a project in robotics that aims to achieve end-to-end risk-awareness guarantees by tight integration of the high-level planning layer and the control layer. The research objectives of the project are to develop:
- algorithms that automatically decompose high-level temporal logic specification formulas into high-level plans and requirements for lower-level control layers;
- control algorithms minimizing risk of violating these requirements; and
- a feedback loop from the control layer to the high-level planning layer that allows to quantify risk-awareness with respect to satisfaction of the high-level specification.
Deadline : 02.Oct.2023
(18) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in cell factory engineering for production of AAV-based gene therapies
Gene therapy development is rapidly advancing and in recent years several therapeutics based on adenoassociated viruses (AAVs) have reached the market. However, one major limitation is that these drugs are difficult to produce and often have a low degree of encapsidated therapeutic genes. This makes AAV bioproduction expensive and unsustainable. We are currently recruiting a PhD student to map cellular processes during bioproduction of AAVs to shed light on what host-cell proteins are interacting with AAVs and impacting the degree of filled viral vectors and the release of viruses from the cells. The person we are looking for will work with viral vector production in mammalian cells as well as quantification and analysis of viral particles. The project will involve different methods such as RNA sequencing analysis, molecular cloning, ELISA, western blotting, qPCR and single cell cloning. We are looking for person that is driven, has good analytical skills and we prefer that you have experience in laborative work.
Deadline :30.Sep.2023
(19) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Energy and Environmental Systems
This research project aims at developing integrated actions and feasible solutions for a circular recovery model for managing municipal solid waste (MSW) in cities. There is an urgency to design and implement a circular recovery model for making urban economies viable and carbon neutral. The project delves into the value chains of MSW, encompassing various stages such as generation, resource recovery, collection, conversion technologies, and the creation of businesses and markets. The project addresses the question of how cities can effectively tackle economic and environmental challenges to minimize their impact in a world with finite resources. You will be responsible for the following tasks: (a) to analyze the techno-economic analysis of waste-to-energy conversion technologies, (b) to identify best practices for the management of MSW in a circularity concept, (c) to develop a scenario-based geospatial and optimal model for an integrated assessment of the circular recovery model, and (d) to showcase a net zero-waste road map for viable smart cities
Deadline : 29.Sep.2023
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(20) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Integrated Energy System Analysis for Sustainable Development
The division of Energy Systems (dES) within the Department of Energy Technology at KTH has received a grant from the Horizon Europe project EPIC AFRICA. The project aims to support the development of robust energy systems in sub-Saharan Africa, taking into account sustainable development in all its dimensions. For this purpose, the project works with stakeholder collaboration and system optimization of the Volta and Tana River resources, to support both energy extraction through hydropower and agricultural development in the regions. As a PhD student, you will mainly work with resource optimization in long-term scenarios to investigate sustainable ways to develop electricity production, possibly with hydrogen storage, sustainable use of water resources, and active agriculture. The models are built in the OSeMOSYS tool, are based on linear programming and open source code.
Deadline : 29.Sep.2023
(21) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student (licentiate) in Data-driven fluid and climate theory
This research project aims to realize faster-than-real-time (simulation time less than physical flow time) and high-resolution simulation of fluid flow in engineering applications, with indoor climate as a pilot. The expected outcome of this project is a static CNN for super-resolution to achieve fast prediction of steady-state indoor airflow, a hybrid RCNN for super-resolution to achieve faster-than-real-time prediction of transient indoor airflow, and standards for low-resolution input data by numerical simulation and experimental data. Besides the indoor flow simulations, this project would open a broad spectrum of engineering accurate computational fluid dynamics (CFD) applications, complementary to today’s standard application of RANS turbulence models. The researchers in the team represent the KTH of Architecture and the Built Environment， Department of Civil and Architectural Engineering and KTH School of Engineering Sciences, Department of Engineering Mechanics.
Deadline : 29.Sep.2023
(22) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Networked Systems Security
We invite applications for doctoral student positions with the Networked Systems Security (NSS) lab at EECS/SCS. 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 :29.Sep.2023
(23) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in catalytic conversion of biooil from pyrolysis of wastes
This PhD project will focus on the investigation of catalytic conversion of pyrolysis oil, produced via pyrolysis of waste from agriculture and forest industry. The research is of importance to further develop and improve fast pyrolysis processes for effective and sustainable conversion of biogenic wastes, enabling a transition to a sustainable energy system. You will work with researchers from different fields (energy- and chemical engineering), universities/institutes (national and international), and with equipment/process technology owners. The PhD candidate will (i) characterize different catalyst materials before and after use in a catalytic reactor (ii) conduct experimental trials in a 5-kW fluidized bed setup (iii) analyze product compositions. Examples of analysis and characterization techniques are GC/MS, HPLC, FTIR, H-NMR, ICP-OES, SEM/EDX, BET, TGA/DSC with SID, TPD/TPO/TPR, etc. The PhD candidate will work within a project financed by EU: Pyragraf – Decentralized pyrolytic conversion of agriculture and forestry wastes towards local circular value chains and sustainability. In your research, you will collaborate (among others) with researchers at KTH, Karslruhe Institute of Technology (KIT) in Germany, and the technology owner Topsoe A/S in Denmark.
Deadline : 28.Sep.2023
(24) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Wireless Industrial Networking
In this project, the focus will be on wireless industrial networking at scale. 5G standards introduce various features that specifically target the industrial automation sector. The introduction of these features leaves a large space for optimization, leading to interesting trade-offs and novel challenges. The PhD project will be devoted to these aspects, leveraging mathematics, simulation as well as implementation platforms. The project is in a larger context, and hence collaboration within the research group on this topic will be essential. Our research group has a track record in leading academic research with real-world impact in the area of industrial wireless networking. We are looking for an outstanding individual interested in integrating with a strong team as well as with external stakeholders in order to shape the field. We typically combine fundamental research work (leveraging methods from communication and queuing theory) with experimental testbed development and trials. More and more focus of our group is also put on machine learning in combination with wireless networking.
Deadline : 28.Sep.2023
(25) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in participatory urban energy modelling
This PhD position is proposed within the project ‘Integrating data-driven decision-support, energy models and data analytics in urban transition governance’. The project will study possibilities for the use of urban data in a more reflective and needs-oriented way to enable informed decisions in the transition to climate-neutral cities. It builds upon the Oden data ecosystem – the fusion of data, models and decision-support tools for urban building energy data analytics in Stockholm and other Swedish cities. This project will focus on a ‘real-life’ case study of large-scale implementation of energy efficiency measures across an urban district in Stockholm.
Deadline : 28.Sep.2023
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.
KTH is the highest ranked technical university in Sweden. It is ranked top 100 in the world among all universities in the 2020 QS World University Rankings.
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