Student Assistant Positions in a research project


on the use of machine learning for training load management in top-level sports

This project will bring together methodological competence in statistics, machine learning and computer science with current developments in sport sciences as well as technological progress in wearables and medical diagnostics in order to optimize training load of top athletes in endurance sports. The project will start as a pilot project in cooperation with the Austrian Rowing Federation (termed “AIROW – Artificial Intelligence in Rowing”) and will later be extended to other sports, such as swimming, triathlon, cycling and mid-/long distance running. It will likely be funded by the “Bundesministerium für Kunst, Kultur, öffentlicher Dienst und Sport“.

In the project, we will collect and process „big data“ from training and performance processes of individual athletes and will use state-of-the-art machine learning technology in order to measure effective training load, to predict the effect of training impulses and to optimize training management. The project will bring together researchers from statistics, computer science, mathematics, sports science and sports medicine. While being practically highly relevant in order to strengthen the competitiveness of Austrian top-level sports, the project will be scientifically challenging and will produce novel insights and findings.

Currently, we are looking for students with knowledge on the interface between statistics and computer science, particularly experience in front end development (R Shiny, HTML, Sass, CSS, JavaScript, D3, Vue.js, WebGL, Tableau, ) and database management (SQL, NoSQL). At a later stage, we are looking for students with background in statistics/data science. Working contracts can be for 10h/week up to 20h/week. The project work may also result in a seminar project or thesis paper – depending on the particular tasks and topics.

Interested students may contact Prof. Dr. Nikolaus Hautsch,