ORGANISATION/COMPANYUniversity of Twente (UT)
RESEARCH FIELDCultural studiesTechnology
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE01/07/2020 00:00 - Europe/Brussels
LOCATIONNetherlands › Enschede
TYPE OF CONTRACTTemporary
HOURS PER WEEK38.0
The department of Electrical Engineering, Mathematics, and Computer Science (EEMCS) of the University of Twente (UT) has an opening for three full-time, 4-year, fully-funded PhD students to strengthen the newly started Theme Team in Sports, Data and Interaction. The project concerns sense-making of, and interaction with, sensor data from athletes in running, rowing, and volleyball. The PhD candidates will be embedded in the research groups Human Media Interaction (HMI), Biomedical Signals and Systems (BSS), and Mathematics of Operations Research (MOR), respectively, and will work closely together during the project.
We encourage the PhD students to perform high quality and internationally visible research that gets published at top tier conferences and journals. This highly interdisciplinary research project seeks to improve sports training and education through the use of data through three main lines of innovation:
- innovation of data science for automatic tracking and analysis of movement and behavioural data in sports,
- innovation in statistical tools for modeling behavioral patterns and anomalies in individual cyclical sports and in non-cyclical (team) sports, and
- innovation in interaction technology for interactive sensemaking of the data for trainers and athletes and for novel interactive, digital-physical forms of training based on the data.
We target a range of users, from elite players to youth and recreational sports, and including players as well as trainers.
The three positions focus on distinct, but closely aligned subtasks of the project, as described below.
Position 1 Sensors and measurement for sports activities
Sports behaviour and movement patterns in cyclic sports like running (predictable patterns) and pivoting sports like volleyball (less predictable patterns) are measured using various ambulant and body worn (inertial) sensors. Sensor data can be used for a better understanding of (changes in) these patterns (e.g. due to fatigue) to prevent injuries or improve (team) performance. This is currently limited however to single stream, non real-time, off line analysis. To progress beyond the state of the art requires the development of novel algorithms and tools to link, merge and enrich data sets, do real time analysis, provide feedback and progress from single to multiple data streams. The challenge is to detect changes in data streams in real time, build context and to merge data streams from multiple sensors.
This candidate will focus on automatic analysis of behavioural data in sports exercises using minimized on-body sensing modalities. This analysis will be translated into novel tools for modelling the athlete behaviour in context, the coordinated behaviour within the team, and the temporal development of this behaviour. The data collection, analysis and modelling work will be done in collaboration with all project members and in an iterative way.
This position has already been tentatively filled.
Position 2 Statistical tools for modeling sports data
The data that is measured through the various sensors, has to be modeled from a statistical perspective, to find and predict temporal patterns of individual and team behaviours vs. performance and fatigue. This requires, among other things, a novel toolbox of statistical techniques to move from offline prediction (unsuitable for interactive applications) to online, scanning filter based approaches. Challenges are: finding optimal filters and dealing with computational complexity given the extensive amount of data and the increase in complexity of data from univariate time series to dynamic network structures in team sports.
The focus is on developing new statistical tools and approaches to model the sports data in a way that is suitable for use in interactive applications. The candidate will also collaborate to integrate these tools into a computational system for real-time analysis, in close collaboration with the other candidates.
Possible directions to shape the research project are
- Anomaly detection
- nonparametric statistics and machine learning
- time series analysis, specifically change-point detection
- Simultaneous inference
The position is part of the Statistics group.
Position 2 profile
You have acquired a Master’s degree in mathematics, statistics, data science or a closely related domain with a strong background in mathematics and statistics, as well as some programming skills in R or Python.
You have a creative and curious mind, a clear interest in interdisciplinary research and are passionate to work on these topics.
Good communication skills in the English language are required
More information on position 2
- Katharina Proksch – firstname.lastname@example.org
Position 3 Novel interactive, digitally enhanced training environments
The modeled data will be used in real time, interactive training and performance context in which we adaptively influence, in a systematic and controlled way, the athlete’s performance in relation to effort, quality, and fatigue. This will improve sports performance but also contribute to injury prevention: more resilience in sports training and performance thanks to novel data science! Challenges are to develop systems and models of interaction that create tailored learning rich situations through well chosen technology and accompanying feedback and interactively adaptable exercise environments, and evaluating the impact thereof on the athlete.
In this position you will work on developing new interaction technology for interactive sense-making of the data for trainers and athletes and for novel interactive, digital-physical forms of training based on the data. You will also work on evaluating user experience, perception and performance in explorative and experimental studies. This will be done iteratively, in close interaction with end users such as trainers and athletes.
The position is part of the Human Media Interaction (HMI) group.
Position 3 profile
You are passionate about the above topics and have a relevant background. You hold an MSc degree in computer science, biomedical engineering, HCI, interaction technology, game design or another relevant domain. You are capable of designing and realizing interaction technology systems. An additional background in user centered research and design, games, or embodied interaction is considered a pre.
You are keen to become an independent and self-directed researcher and developer, but also are a great teammate with good communication skills and able to work in a diverse and multidisciplinary setting. You have independent research and publication skills can contribute to the realization of actual interactive technology systems.
More information on position 3
We offer an exciting research position in a dynamic and international environment, combining the benefits of academic research with a topic of high societal relevance. The UT offers excellent working conditions, a dynamic scientific environment, and a green and lively campus with lots of sports facilities and an international scientific community.
- You will be appointed on a fulltime PhD position for four years, with a qualifier in the first year.
- You will have a full status as an employee at the UT, including pension and health care benefits.
- Your salary will range from EUR 2.395,- (1st year) to EUR 3.061,- (4th year) per month, plus holiday allowance (8%) and end-of-year bonus (8.3%).
- You can make use of excellent facilities for professional and personal development.
- You will receive good secondary conditions, in accordance with the collective labour agreement CAO-NU for Dutch universities.
Web site for additional job details
Information and application
Do you want to work at the Best Technical University in The Netherlands, praised by the Keuzegids in 2019?
We look forward to receiving your online application via the "Apply now" button below, with the following documents before June 30th, 2020. Your application must include:
- A cover letter (maximum 2 pages A4), emphasizing your specific interest, qualifications, motivations to apply for this position and research ideas for the PhD project.
- A full Curriculum Vitae, including a list of all courses attended and grades obtained, and, if applicable, a list of publications.
- A short description (maximum 1 page A4) of your MSc research.
The selection procedure includes an assessment, interview and scientific presentation.
- Application deadline: June 30th
- Job interviews: Early July
- Decision: Mid July
- Starting date: ~September
For additional information about these positions, you are encouraged to contact the researchers mentioned above.
EURAXESS offer ID: 530369
Posting organisation offer ID: 292328
The responsibility for the jobs published on this website, including the job description, lies entirely with the publishing institutions. The application is handled uniquely by the employer, who is also fully responsible for the recruitment and selection processes.
Please contact email@example.com if you wish to download all jobs in XML.