LABDA (Learning Network for Advanced Behavioural Data Analysis) is an EU-funded MSCA Doctoral Network, that brings together leading researchers in advanced movement behaviour data analysis at the intersection of data science, method development, epidemiology, public health, and wearable technology to train a new generation of creative and innovative public health researchers via training-through-research. The main aims of LABDA are to establish novel methods for advanced 24/7 movement behaviour data analysis of sensor-based data, examine the added value of advanced behavioural data analysis and multi-modal data for predicting health risk and facilitate the use and interpretability of the advanced methods for application in science, policy and society. Via training-through-research projects, 13 doctoral fellows will contribute to reaching these aims. Together, they will develop a joint taxonomy to enable interoperability and data harmonisation. Results will be combined in an open-source LABDA toolbox of advanced analysis methods, including a decision tree to guide researchers and other users to the optimal method for their (research) question. The open-source toolbox of advanced analysis methods will lead to optimised, tailored public health recommendations and improved personal wearable feedback concerning 24/7 movement behaviour. For more information, see the project's website:
LABDA projectAbout your roleAs a PhD student in the project 'Translation of advanced 24/7 movement behaviour data to real-life behaviour and public health recommendations' your challenge is to characterise behaviour profiles across subgroups using advanced methods with an intersectional approach, and to translate optimal behaviour profiles into public health recommendations. Your work will result in the contextual description of behavioural profiles of different subgroups, taking into account various characteristics including age, gender, ethnicity, and socio-economic position. In addition, you will develop an advice for developing public health recommendations based on advanced methods.
Your tasksYour specific responsibilities will be to:
- Design and apply a mixed-methods approach to the project;
- Characterise behavioural profiles using existing cohort data based on advanced behavioural data analysis tools;
- Apply an intersectionaly lens throughout all phases of the PhD project;
- Engage with all stakeholders relevant to the translation of 24/7 movement behaviour throughout the PhD project;
- Report on findings by publishing scientific articles, resulting in a dissertation;
- Present findings at (inter)national meetings/conferences;
- Collaborate and exchange knowledge and skills with the other LABDA fellows;
- Contribute to the LABDA toolbox of advanced analysis methods for sensor-based behavioural data;
- Contribute to educational activities of the department and within the consortium.