Marie Curie PhD Position - Analysis of multi-source advanced behavioural data

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Declaration of interest regarding PhD project:

SENS Innovation ApS and the Department of Sports Science and Clinical Biomechanics, research unit for Active Living at SDU are looking for applicants for a PhD scholarship within the Marie Skłodowska-Curie Doctoral Network ‘Advanced behavioural data analysis’ funded by the European Union’s Horizon Europe research and innovation programme (grant agreement No.101072993). The PhD project is expected to start in October 2023 and employment will be for 36 months.

The LABDA project

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: www.labda-project.eu.

What will you do

You will be part of a development team working on the next generation of enriched accelerometer-based data collection systems, and as such be instrumental in the development of a smart-phone application to see your work implemented in real life products.

As an industrial PhD student in the project ‘multi-source time series data analysis’ your challenge is to extend the SENS motion state-of-the-art activity sensor data with contextual data such as smart phone GPS position, ecological momentary assessment (EMA) functionality and user insights collected through the existing SENS motion app.

Your work will be key to improve classification accuracy and/or add contextual information central to providing a world leading scalable platform for collection of physical activity data.

Your tasks

Your specific responsibilities will be to:

  • Systematically assess the benefits and drawbacks of existing multi-source movement behaviour data methods where accelerometer data are combined with other data to improve classification accuracy and/or add contextual information
  • Further develop an existing smartphone application to be able to combine accelerometer data with contextual data collected using GPS and/or EMA functionality
  • Assess if the behavioural classification accuracy can be improved using data from the additional sources and if yes, implement the improved classification algorithm
  • Conduct a feasibility test with the improved multi-source movement behavior data collection method
  • Report on findings by publishing scientific articles, resulting in a dissertation
  • Present findings at (inter)national meetings/conferences
  • Contribute to the LABDA toolbox of advanced analysis methods for sensor-based behavioural data
  • Contribute to educational activities within the consortium

Qualifications

We are looking for an ambitious PhD candidate with the following qualifications:

  • Master’s degree in human movement sciences, data science or a related discipline
  • Previous experience in analysing accelerometer data is a plus
  • Proficient with programming languages (e.g. in Python, R, MATLAB)
  • Preference to work in an interdisciplinary, collaborative, inclusive environment
  • Excellent communication and collaboration skills and fluent in English

To be eligible, candidates need to fulfil the MSCA basic requirements:

  • All researchers recruited in a Doctoral Network must be doctoral candidates, i.e. not already in possession of a doctoral degree at the date of the recruitment
  • Doctoral candidates must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting host organisation for more than 12 months in the 3 years immediately before the recruitment date. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status under the Geneva Convention are not taken into account

For more information about the recruitment process, see: https://www.labda-project.eu/vacancies/process.html.

Research environment

You will be employed by SENS Innovation ApS Denmark (led by Morten Kjærgaard and Kasper Lundberg Lykkegaard) and you will enroll as a PhD student at the Faculty of Health Sciences, University of Southern Denmark (SDU) with Professor Jasper Schipperijn from the Department of Sports Science and Clinical Biomechanics as PhD supervisor. For more information see www.SDU.dk/en/activeliving.

Your main place of work will be SENS Innovation ApS, Nannasgade 28, 2200 Copenhagen N. For more information see www.sens.dk.

As part of the project you will go on secondments to:

  • Department of Sports Science and Clinical Biomechanics, SDU, Odense, Denmark,: to exchange knowledge and gain experience in working with combined GPS and accelerometer data (collaborator Schipperijn)
  • Norwegian University of Science and Technology (NTNU, Trondheim, Norway): to explore if the additional data sources can be used in the algorithms to increase classification accuracy (collaborator Bach)
  • Loughborough Uinveristy (LU, Loughborough, UK) to be trained in collecting and optimizing EMA data, as well as refining the feasibility test protocol (collaborator Sherar)

Working at SENS Innovation means being part of a scale-up in rapid growth. We are a dynamic team, and offer you ample opportunity for development, deepening and broadening, additional training and a place to grow! SENS Innovation is on a journey, from a small start-up company with just a few employees to an international player in the market of physical activity monitoring.

Being enrolled as PhD student at the Faculty of Health Sciences, SDU, Department of Sports Science and Clinical Biomechanics, means that you will be part of a dynamic research environment with over 10 years of experience of working with accelerometer-based multi-source time series data analysis. Two other PhD students within the LADBA project will be enrolled and employed in the same team and will be working on closely related projects.

For further information about the project, please contact:

Kasper Lundberg Lykkegaard
SENS Innovation ApS
E-mail: [email protected] or phone: +45 26238234

Professor Jasper Schipperijn
Department of Sports Science and Clinical Biomechanics, University of Southern Denmark
E-mail: [email protected] (preferred) or phone: +45 20782540

Applications must include:

  • At letter stating the interest, motivation and qualifications for the project (max. 2 pages) - upload under “Application form”
  • Detailed CV, including personal contact information, and contact information for 2 references
  • Certified copy of diploma (Master’s degree in a relevant field)

Applications must be submitted electronically using the link "Apply online".

Attached files must be in Adobe PDF or Word format. Each box can only contain a single file of max. 10 Mb. If you are not asked for a project description above, please upload and empty document in the field “projektbeskrivelse”.

Incomplete applications and applications received after the deadline will neither be considered nor evaluated. This also applies to reference letters. Applications will be shared with external partners.

Closing date, April 10, 2023

Successful candidates will be asked to send an application for enrollment to the PhD Secretariat, Faculty of Health Sciences, to be enrolled as PhD students.

The PhD programme will be carried out in accordance with Faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order)

The terms of employment as a salaried PhD Research Fellow are stated in the Agreement between the Ministry of Finance and the Danish Confederation of Professional Associations (AC).

We like our staff to reflect the diversity of society and thus welcome applications from all qualified candidates regardless of personal background.


Information og data

Denne ledige stilling har jobtypen "Forsker", og befinder sig i kategorien "Sundhed og forskning".

Arbejdsstedet er beliggende i Hele Danmark

Jobbet er oprettet på vores service den 16.3.2023, men kan have været deaktiveret og genaktiveret igen.

Dagligt opdateret: Dette job opdateres dagligt ud fra jobudbyderens hjemmeside via vores søgemaskineteknologi og er aktivt lige nu.
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  • Mandag den 10. april 2023

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