09 Fully Funded PhD Programs in Computer Science at KU Leuven, Belgium

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Are you holding Master’s degree and looking for PhD positions? KU Leuven, Belgium inviting online application for funded PhD Programs / fully funded PhD positions. 

Interested and eligible applicants may submit their online application for PhD programs via the University’s Online Application Portal.

1. PhD Position in From static to dynamic Inland Electronic Navigation Charts (IENC)

Summary of PhD Program:

The Robotics research at KU Leuven Department of Mechanical Engineering has pioneered robotics research in Europe since the mid-1970s. It has covered virtually all aspects of sensor-based robotics, from the high-level task specification down to low-level sensor-based control, and applied the research results in a variety of industrial applications.

In the last decade the group shifted its attention towards advanced industrial robot assistants, and active sensing. The Intelligent Mobile Platform (IMP) group is a multi-disciplinary and multi-campus research group originating from the robotics research with a focus on the intelligent design and control of the mobile platforms of the future with a special focus on waterway transport applications.

The industrial relevance of the department’s research activities is witnessed by its many spin-off companies and its tradition of close industry collaboration in numerous European, national, and bilateral projects.

Last Application Date: November 1, 2022

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2. PhD Position in Knowledge-based AI for Manufacturing

Summary of PhD Program:

In this PhD, you research innovative ways of intelligently supporting machine operators in the manufacturing industry. For this, you will develop a knowledge-based AI system, which applies different forms of logical reasoning to the domain knowledge of experts. This research builds on results from previous projects within the research group, such as, for example, a prototype that helps engineers design machine parts. In this project, we will use similar technology to help operators adjust machines.

Last Application Date: October 7, 2022

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3. PhD Position in Insightful modelling and algorithm development for nurse rostering

Summary of PhD Program:

Efficient algorithms for complex personnel scheduling problems are critical for ensuring organisations can provide a suitably qualified workforce at minimal cost while satisfying a wide variety of strict regulations meeting occupational health and safety requirements, as well as employee preferences.

This PhD project will focus on nurse rostering, where nurses must be optimally allocated to work shifts in a manner that ensures their specialised expertise is available when required to support scheduled surgeries and other activities, while satisfying rules about shift lengths, leave days, and accommodating as much as possible their individual preferences.

The University of Melbourne has strong expertise in tackling related scheduling problems, but will benefit enormously from the specific expertise of the KU Leuven team developed over several decades in advancing models and algorithms for the nurse rostering problem. The partnership will enable new collaborative links with Melbourne based hospitals to be forged to support this PhD project, via the new ARC Training Centre in Optimisation Technologies, Integrated Methodologies and Applications (OPTIMA), in which the PhD student will be based.

The KU Leuven team will also benefit from application of the University of Melbourne’s Instance Space Analysis methodology to gain deep insights into the strengths and weaknesses of nurse rostering algorithms, and ensure that the project’s newly developed algorithmic advances are rigorously “stress tested” to understand their robustness and reliability for a wide range of hospital settings in both Australia and Belgium.

Last Application Date: October 30, 2022

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4. PhD Position in Characterizing input composition by statistical learning

Summary of PhD Program:

In the steel production process, two important ingredients are combined: pig iron (or crude iron) and scrap (recycled metal materials). Depending on the scrap quality, which is determined by the concentration of impurities such as sulfur, the amount of scrap going into a single production batch can be adjusted. By better characterization of scrap input impurities it is possible to reduce CO2 emissions by using less pig iron.

The aim of this PhD position is to develop methods and algorithms to model the distributional properties of sulfur and other impurities in the different scrap piles, based on available measurements which are present in the current steel production process. For this, you will be in close contact with modelling specialists from ArcelorMittal Belgium.

You will apply a number of state-of-the-art methods and algorithms and determine which method is the most suitable to track the interesting properties of the scrap piles and include ways to manage their uncertainties. This will involve Markov Chain Monte Carlo and Gaussian process techniques, whose efficiency will depend on the quality and the features of the data. Validation of the methods can be performed by effective measurements on the scrap piles.

Last Application Date: October 28, 2022

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5. PhD Position in interactive architecture / robotic furniture

Summary of PhD Program:

The current post-pandemic office is unable to fulfill the needs of workers, who expect their workspace to establish a shared social culture, support team activities and provide shelter for focused work. Although a typical office space provides the environment, infrastructure and equipment that could accommodate these needs, they are not flexibly used because the presence and activities of workers have become too unpredictable to facilitate for.

The project envisions a fully responsive workplace that adapts, learns and grows with its users. It will develop robotic furniture that can dynamically adapt the architectural layout to the individual and communal wellbeing of the workers. For instance, in this workplace, interior partitions could semi-autonomously move in order to facilitate certain work activities, optimize environmental conditions or nudge social interactions between workers.

Last Application Date: October 9, 2022

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6. PhD Position in Smart Sensors for Shape-Adaptable Shoe Insoles for Diabetic Patients

Summary of PhD Program:

For diabetic patients, special care needs to be given to the extremities in the body such as the foot. Therefore, shoe insoles are carefully designed to minimize the pressures on the foot during daily activities. However, there is still a need for a reactive patient-targeted approach. In this Ph.D. project, the candidate will investigate new technologies for sensing coatings with the application in shoe insoles to design flexible electronics to sense and detect excess local pressures.

The design and development of sensing coatings and electronics is very challenging as pressures need to be measured with high sensitivity at a high load. Graphene-based sensors have shown a lot of promise in achieving this. The candidate will therefore investigate how graphene-based sensors can be applied in coatings in shoe insoles to meet the sensing requirements.

Furthermore, the candidate will need to design energy-efficient and accurate electronics and software to detect these pressures. Furthermore, the candidate will also design a custommade and energy-efficient electronics to capture signals from this sensor. The candidate will work in the context of the ORTEADA project and will join a multidisciplinary team of professors with various backgrounds and 2 other Ph.D. students. The candidate will collaborate with Ph.D. candidates on the topic of Material Sciences and Rehabilitation of the diabetic foot.

Last Application Date: October 28, 2022

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7. PhD Position in Uncertainty quantification in consumption patterns and flexibility of thermal loads

Summary of PhD Program:

Advanced control strategies, and model predictive control (MPC) in particular, are gaining widespread interest for building climate control, since they can systematically save energy and/or costs with simultaneous thermal comfort improvement, as well as adapt the energy demand according to the available renewable/residual supply.

MPC however suffers from (1) parametric uncertainties, which are uncertainties that can be decreased (though not fully eliminated) by adaptation improvement of model parameter (e.g., through learning), and (2) additive uncertainties (such as forecast uncertainty) that cannot be substantially decreased but that can be dealt with in the decision-making process. These substantially limit the performance of MPC approaches.

Several computational methods to handle uncertainties in mathematical models have recently been developed at NUMA; for example, quasi-Monte Carlo methods in forward uncertainty quantification for PDEs with random diffusion coefficients. Quasi-Monte Carlo methods are multivariate quadrature methods which are especially suitable for higher dimensional integrals/expectations, having the possibility of vanquishing the curse of dimensionality under certain conditions.

Last Application Date: December 16, 2022

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8. PhD Position in modeling Electron Cyclotron Heating plasmas with SOLPS-ITER

Summary of PhD Program:

The PhD researcher will be part of the Thermal and Fluids Engineering (TFE) research group of prof. Martine Baelmans, in close collaboration with Dr. Tom Wauters from the ITER International Organization located in Cadarache, France. The TFE group is embedded in the Mechanical Engineering Department of KU Leuven, Europe’s most innovative university [Reuters]. The TFE group focuses on modeling and optimization in plasma physics, fluid mechanics, and heat transfer.

In the field of plasma edge modeling, the group is renowned as one of the main developers of the SOLPS-ITER code, used worldwide for the interpretation of exhaust scenarios on existing fusion experiments, and for the design of future fusion reactors. The group pioneered the use of adjoint-based optimization for divertor design in this research domain.

Recent work focussed on plasma edge simulations up to the vessel wall, SOLPS-ITER code modernization, speed-up and convergence studies, development of hybrid fluid-kinetic neutral models for reactor studies, development of self-consistent anomalous transport models and model calibration for plasma edge codes.

Last Application Date: October 31, 2022

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9. PhD Position in secure software stacks for decentralized applications

Summary of PhD Program:

In this position you will perform research on decentralized applications under the supervision of prof. Tom Van Cutsem. Our research aims to cover the full stack of building secure decentralized applications, from the blockchain layer to the smart contract execution layer all the way up to the application logic. We study both existing platforms (e.g. Ethereum, Cosmos) as well as create the foundations for next-generation Dapp platforms. The specific scope of your research project is open for discussion.

Last Application Date: November 15, 2022

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