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 Micromachined Microwave/THz Communication Systems
The project focuses on new hardware technology for enabling future telecommunication systems approaching terahertz frequencies. Highly miniaturized, MEMS-reconfigurable and high performance communication front-ends are to be demonstrated from 500 GHz to beyond 1 THz, enabled by micromachined waveguide systems integrated in a single silicon chip. Novel communication architectures are to be investigated for this frequency range. The project is a collaboration between KTH and Chalmers and is supported by six industrial partners. The project is funded by the Swedish Foundation for Strategic Reseach (SSF).
Deadline : 23.May.2022
(02) PhD Degree – Fully Funded
PhD position summary/title: Doctoral students in Scalable and Distributed Reinforcement Learning
We are currently looking for up to two doctoral students with a very strong background and interest in mathematics (statistics and probability theory) and machine learning. The successful candidates will work on a recently granted national project on Reinforcement Learning (RL). In the project, we will develop new theories and methods towards the design of faster and more robust RL algorithms. The doctoral program in Electrical Engineering provides world-class quality education, including a large list of graduate courses ensuring an in-depth development of relevant competencies and skills. The position is within the research group of Prof . Alexandre Proutiere, at the Division of Decision and Control Systems.
Deadline : 30.May.2022
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(03) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in applied mathematics, specialisation in deep learning
Third-cycle subject: Applied and Computational Mathematics, specialization Numerical Analysis
The project aims to develop theory and methods from deep learning for modelling protein structure and dynamics in 3D electron microscopy, see https://www.kth.se/profile/ozan/page/phd-position-deep-learning-and-cryo-em
Supervision: Ozan Öktem is proposed to supervise the doctoral student. Decisions are made on admission
Deadline : 13.May.2022
(04) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in spectral turbulent-wing sims & deep-learning methods
The goal of this project is to use computational-fluid-dynamics (CFD) methods for the analysis of turbulent flows around wings and other complex geometries. To this end, high-order spectral methods will be employed to perform both well-resolved large-eddy simulations and direct numerical simulations, in order to assess the influence of pressure-gradient, wall curvature and three-dimensionality in the dynamics of wall-bounded turbulence. We are also interested in using deep-learning methods to further understand the impact of the simulation parameters on the results and to effectively design novel flow-control strategies. The researcher will become part of the VinuesaLab research group (https://www.vinuesalab.com), where he/she will have the possibility to interact with several related projects dealing with large-scale turbulence simulations, deep learning and experiments. Furthermore, he/she will also have access to the multi-peta scale supercomputing facilities available at KTH, in conjunction with the Swedish e-Science Research Centre (SeRC, www.e-science.se). Finally, the researcher will become part of the excellent research environment FLOW (www.flow.kth.se).
Deadline : 13.May.2022
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(05) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Organic Redox Flow Batteries
Redox flow batteries are suitable for medium- and large-scale energy storage in combination with renewable energy sources such as solar and wind. RFBs could be made low-cost and green by using organic redox species. The aim of the project is to characterize novel green organic redox species for RFBs. The research is of importance to improve the capacity and performance of RFBs and, more importantly, to drastically reduce the cost of energy storage for stationary applications compared to all-vanadium RFBs or Li-ion batteries. In the project, the Ph.D. candidate will synthesize and characterize (NMR, FT-IR etc) novel organic redox species in collaboration with the Department of Chemistry, KTH. For this reason, the applicant must have a solid background in organic synthesis. The redox species will thereafter be electrochemically characterized in conventional electrochemical cells and an RFB setup at the Department of Applied Electrochemistry, KTH.
Deadline : 27.May.2022
(06) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in machine learning for robotic manipulation
We are looking for a PhD student to work on the grand challenge of robotic manipulation of deformable/soft objects. The PhD project will aim towards developing hybrid machine learning and computational geometry approaches towards manipulation primitives of such objects in which the underlying configuration spaces are approximated using modern large scale data-driven cell-complex decomposition.
Deadline : 16.May.2022
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(07) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in Data visualization
This project will develop algorithms, methods, and tools to visually analyze data. We focus on topology-based algorithms due to their powerful capabilities for extracting features. Our main challenge is to formulate these algorithms such that they are fast and efficient. We integrate these algorithms in a modern visualization tool.
Our results will allow new scientific questions to be addressed in many research domains, including climate research, material science, fluid dynamics, and others.
Deadline : 31.May.2022
(08) PhD Degree – Fully Funded
PhD position summary/title: Doktorand inom robusta digitaliserade framtida elnät
Framtida elkraftsystem förväntas ha ett högt genomslag av förnybar energi, energilagring, producenter och konsumenter med elektriska bilar, smarta hem och hushållsapparater. När komplexiteten och sektorkoppling i energisystemet ökar, kommer frekvensen av oväntade händelser att öka samtidigt som svängmassan i systemet håller på att sjunka. Dessutom leder ökad digitalisering till att energisystemet i hög grad exponeras för cyberattacker. Säkerheten och resistens av energi-infrastrukturen är avgörande för ett välfungerande samhälle.
Deadline : 2022-05-31
(09) PhD Degree – Fully Funded
PhD position summary/title: Doktorand inom robusta framtida elnät
Framtida elkraftsystem förväntas ha ett högt genomslag av förnybar energi, energilagring, producenter och konsumenter med elektriska bilar, smarta hem och hushållsapparater. När komplexiteten och sektorkoppling i energisystemet ökar, kommer frekvensen av oväntade händelser att öka samtidigt som svängmassan i systemet håller på att sjunka. Dessutom leder ökad digitalisering till att energisystemet i hög grad exponeras för cyberattacker. Säkerheten och resistens av energi-infrastrukturen är avgörande för ett välfungerande samhälle.
Deadline : 2022-05-31
(10) PhD Degree – Fully Funded
PhD position summary/title: Doctoral student in high-performance machine-learning
This research project aims at developing the principles behind the next generation of computing systems optimized for modern data-intensive workloads. We believe that these systems will make a disruptive departure from the classic Von Neumann architecture, with its decoupling of memory and computing, and embrace the principle of processing-near-memory. In this way, it is possible to shortcut the main limitations of current hardware systems. Your role will be to explore how ML algorithms and computer architectures can be enhanced and radically re-designed for unprecedented efficiency and scalability.
Deadline : 31.May.2022
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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.
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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