PhD Position in Machine Learning Models for Indoor Person Monitoring using Radar Signals
Catholic University of Leuven
Belgium

 
Radar signals are a rich source of information that have ample perspective to glean useful insights about the monitoring context. Automating the interpretation of time-series data (such as radar signals) is a primary focus of the KU Leuven Advanced Integrated Sensing lab (ADVISE) research group which resides in the Faculty of Engineering Technology at KU Leuven Geel Campus. A wide range of real-life applications are being targeted such as contactless radar-based monitoring of human activities, vital signs and person localization. In total a group of 7 PhD researchers and 1 post-doc are currently involved in this research track which is being coordinated by Prof. Peter Karsmakers (https://www.kuleuven.be/wieiswie/en/person/00047893). This group is part of the Computer Science Department of the KU Leuven and has a strong link with the DTAI research team (https://dtai.cs.kuleuven.be). For the projects involving radar technology DTAI-ADVISE collaborates with the research group ESAT-TELEMIC from the KU Leuven and more specifically with prof. Dominique Schreurs (https://www.kuleuven.be/wieiswie/nl/person/00009846) who is heading a subgroup that consists of about a dozen persons (PhD students, post-docs, technical and administrative staff), and focuses on modeling, measurement, and design of microwave and millimeter wave devices, circuits and systems for telecommunications and healthcare applications.

Project

We are hiring a PhD candidate to participate in the “NextPerception” European H2020-ECSEL project that targets next generation smart perception sensors and distributed intelligence for proactive human monitoring in health, wellbeing, and automotive systems. Together with 3 Flemish companies the main goal is to develop (distributed) algorithms that can track the movement events, vital signs and locations of multiple person that are active in the same indoor location. Although some signal processing will be required the main focus of the candidate will lie on using machine learning methods to achieve the desired goals. The researcher can start from the strong knowledge that our groups have regarding detecting fall incidents of elderly people and vital sign monitoring using the in-house developed SFCW radar. In this project also commercially, available radars will be explored. Moreover, it will be investigated to which extent fusing information coming from the radar together with that acquired by a worn IMU sensor gives added value to the person monitoring system. The research will be mainly be carried out at Geel campus (DTAI-ADVISE research team) with regular visits to campus Heverlee (ESAT-TELEMIC research team).

Profile

If you recognize yourself in the story below, then you have the profile that fits the project and the research group.
  • I have a master’s degree in engineering, computer science, physics or mathematics and performed above average in comparison to my peers.
  • I’m proficient in written and spoken English.
  • You are highly interested in working with health-related data. 
  • During my courses or prior professional activities, I have gathered some basic experience with signal processing, machine learning and radar technology, and/or I have a profound interest in these topics.      
  • As a PhD researcher I perform research in a structured and scientifically sound manner. I read technical papers, understand the nuances between different theories and implement and improve methodologies myself. 
  • Based on interactions and discussions with my supervisors and my team colleagues, I set up and update a plan of approach for the upcoming 1 to 3 months to work towards my research goals. I work with a sufficient degree of independence to follow my plan and achieve the goals. I indicate timely when deviations of the plan are required, if goals cannot be met or if I want to discuss intermediate results or issues.
  • In frequent reporting, varying between weekly to monthly, I show the results that I have obtained, and I give a well-founded interpretation of those results. I iterate on my work and my approach based on the feedback of my supervisors which steer the direction of my research.
  • I value being part of a large research community and I am eager to learn how academic research can be linked to industrial innovation roadmaps.
  • During my PhD I want to grow towards following up the project that I am involved in and representing the research group on project meetings or conferences. I see those events as an occasion to disseminate my work to an audience of international experts and research colleagues, and to learn on the larger context of my research and the research project.
  • Experience with scientific data processing software such as Python is a plus.

Offer

  • A remuneration package competitive with industry standards in Belgium, a country with a high quality of life and excellent health care system.
  • A chance to pursue a PhD in Engineering, typically a 4 year trajectory, in a stimulating and ambitious research environment.  
  • Ample opportunity to develop yourself in both a scientific or an industrial direction, besides opportunities provided by the research group, further doctoral training for PhD candidates is provided in the framework of the Leuven Arenberg Doctoral School (https://set.kuleuven.be/phd), known for its strong focus on both future scientists and scientifically trained professionals who will valorise their doctoral expertise and competences in a non-academic context. More information on the training opportunities can be found on the following link: https://set.kuleuven.be/phd/dopl/whytraining. 

Interested?

To apply for this position, please follow the application tool and enclose:
1.full CV – mandatory
2.motivation letter – mandatory
3.full list of credits and grades of both BSc and MSc degrees (as well as their transcription to English if possible) – mandatory (when you haven’t finished your degree yet, just provide us with the partial list of already available credits and grades)
4.proof of English proficiency (TOEFL, IELTS, …) - if available
5.two reference letters - if available
6.an English version of MSc, or of a recent publication or assignment - if available
For more information please contact Peter Karsmakers, by sending an e-mail to peter.karsmakers@kuleuven.be and mention NextPerception Vacancy in the title.
 
You can apply for this job no later than July 20, 2020 via the
KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.
  • Employment percentage: Voltijds
  • Location: Geel
  • Apply before: July 20, 2020
  • Tags: Industriële Ingenieurswetenschappen


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