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Data collection and analysis technician within Mo Re-lab
The position will take place within the Movement and Reality (Mo Re) Lab under the direct supervision of Dr. Daniel Benoit. The Mo Re Lab is a 450sqm state of the art facility. It houses two complete mocap rooms, instrumented treadmill, EMG systems, force platforms, Biodex, and a complete fully functional live-in home environment instrumented with monitoring systems, as well as mobile monitoring systems and an internal network to link all research platforms.
Within the lab group, we strive for a workplace that develops and stimulates all employees. You will belong to research group Sport Sciences, headed by Prof. Eva Ageberg.

Work description
The research conducted in Mo Re-Lab is focused on the interdisciplinary research orientation of Experimental Health Sciences, which uses and develops new ideas and methods in standardized or real environments representing daily life arenas such as housing, pedestrian environments and workplaces, in addition to sports and activities of daily living. Studies aim to develop, test and apply novel methods, develop innovative solutions to optimize functioning in everyday life and expand knowledge of human health and behavior across the life span. In addition, the Mo Re-Lab is used to provide assessments of human functional capacity for a variety of applications outside of research, ranging from clinical assessments of varied patient populations to elite-athlete performance assessments. We utilize technical platforms in such studies and assessments to understand the complex dynamics of physical functioning, behavior, cognition, emotion, and different environmental arenas.

The main task as a data collection and analysis technician will be supporting the lab director and technical director, in particular assisting with data collections, data analysis and report writing. In addition, the person will assist in supporting technical aspects of projects within the Mo Re-lab, including studies and equipment related to human movement analysis, physiological testing, assessment of activities of daily living and mobility, human-environment interaction, and other areas related to the interdisciplinary field of Experimental Health Sciences. This may include the use and development of novel technologies in addition to traditional analysis methods.
You may also work with existing data as well collect new data and help develop new clinical and functional assessment protocols based on evidence derived from this data.

The following work tasks will be included:

• Overseeing/conducting data collection procedures.
• Review of data for quality control, data entry, data analysis, developing data analysis pipelines, report writing, manuscript preparation.
• Assisting with the development of grants, presentations, and publications.

As a member of the Mo Re-lab team, you are also expected to actively participate and collaborate in seminar and meeting activities, lab showings, as well as other external engagements and other duties may also be included.


Requirements and qualifications
You are eligible to be employed as a data collection and analysis technician if you have completed a minimum of Master of Science, but preferred doctoral degree in the subject area of the position.

The following assessment criteria applies:

• Good ability to assist in the development and implementation of high-quality research in musculoskeletal biomechanics, human movement analysis, neuromuscular control, functional assessments, physiological testing or related disciplines.
• M.Sc. or Doctoral degree in biomechanics, kinesiology, sports sciences, health science, biomedical engineering, or a related discipline relevant.
• Proficiency in human movement analysis including motion capture, electromyography, functional assessments and evidence of the ability to independently use the associated instrumentation and software.
• Proficiency in data analysis and report writing of data related to human movement analysis and functional assessments.
• Experience using MATLAB, python or other programming language.
• Experience with statistical analysis
• Excellent English in speech and writing.

We see that you are flexible, take responsibility, and to work independently as well as in a team to assist others with their work and priorities.


Meritorious for the position are:

• Documented experience of qualitative and quantitative research methods.
• Evidence of peer reviewed publications and presentations.
• Experience using machine learning to analyze human movement data.
• Experience researching or testing different populations from across the lifespan
• Good knowledge in spoken and written Swedish, other Scandinavian language or ambition for learning Swedish.

Practical and other
The employment is a part-time position at 50-100% (depending on discussion) and is limited in time according to SÄVA for 12 months, starting on 2024-10-01 or as agreed. There is a chance that the position could develop into a permanent position.
The university applies individual salary setting. Please indicate your desired salary in your application.


How to apply
The position is applied for via the university’s recruitment system. The application should include a cover letter with a motivation for why you are interested in the position and how the position matches your qualifications. The application should also include a CV and other relevant information for the position.
Vi undanber oss alla kontakter från annonsförsäljare, rekryterings- och bemanningsföretag på grund av statliga upphandlingsregler.
Anställningsform: särskild visstidsanställning | Anställningens omfattning: deltid | Antal lediga befattningar: 1 | Sysselsättningsgrad: 50 eller 100 % enligt överenskommelse | Ort: Lund | Län: Skåne län | Land: Sweden | Referensnummer: PA2024/3067 | Kontakt: Kristina Malmquist 046-2220000, Daniel Benoit +46721432898, Eva Ageberg +46462224943, | Facklig företrädare: OFR/ST:Fackförbundet ST:s kansli 046-2229362, SACO:Saco-s-rådet vid Lunds universitet kansli@saco-s.lu.se, SEKO: Seko Civil 046-2229366, | Publicerat: 2024-10-17 | Sista ansökningsdag: 2024-11-03