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PhD student(m/w/x)
Description
In this PhD position, you will explore the relationship between hand function and disease activity in patients with inflammatory arthritis, utilizing motion capture data and clinical information to uncover new biomechanical markers.
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Upload your CV and Nejo AI will find matching job offers for you.
Requirements
- •Above-average Master’s degree or comparable university qualification in medical engineering, sport/movement science, sports technology, biotechnology, computer science or similar fields
- •Experience with motion capture methods (marker-based motion capture and electromyography techniques)
- •Strong knowledge in at least two of the following areas: biomechanics, movement science, statistics, machine learning, programming skills
- •Good understanding of musculoskeletal function and human movement
- •Strong knowledge of human movement and physiology
- •Solid understanding of musculoskeletal function and biostatistics
- •Interest in clinical sciences
- •Good English language skills
- •German language skills sufficient for communication with patients
Education
Tasks
- •Analyze biomechanical hand movements
- •Conduct statistical analysis of relevant parameters
- •Document and report results
- •Collect data on hand function using motion capture, EMG, and clinical tests
Languages
English – Business Fluent
Benefits
Diverse Work
- •Interesting role in a motivated team
- •Participation in international projects
Other Benefits
- •National and international collaborations
- •Possibility of association with FAU graduate schools
Healthcare & Fitness
- •Comprehensive health promotion program
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PhD student(m/w/x)
The AI Job Search Engine
Description
In this PhD position, you will explore the relationship between hand function and disease activity in patients with inflammatory arthritis, utilizing motion capture data and clinical information to uncover new biomechanical markers.
Let AI find the perfect jobs for you!
Upload your CV and Nejo AI will find matching job offers for you.
Requirements
- •Above-average Master’s degree or comparable university qualification in medical engineering, sport/movement science, sports technology, biotechnology, computer science or similar fields
- •Experience with motion capture methods (marker-based motion capture and electromyography techniques)
- •Strong knowledge in at least two of the following areas: biomechanics, movement science, statistics, machine learning, programming skills
- •Good understanding of musculoskeletal function and human movement
- •Strong knowledge of human movement and physiology
- •Solid understanding of musculoskeletal function and biostatistics
- •Interest in clinical sciences
- •Good English language skills
- •German language skills sufficient for communication with patients
Education
Tasks
- •Analyze biomechanical hand movements
- •Conduct statistical analysis of relevant parameters
- •Document and report results
- •Collect data on hand function using motion capture, EMG, and clinical tests
Languages
English – Business Fluent
Benefits
Diverse Work
- •Interesting role in a motivated team
- •Participation in international projects
Other Benefits
- •National and international collaborations
- •Possibility of association with FAU graduate schools
Healthcare & Fitness
- •Comprehensive health promotion program
About the Company
Uniklinikum Erlangen
Industry
Healthcare
Description
Das Medizinische Zentrum für Informations- und Kommunikationstechnik (MIK) betreut die IT-Anforderungen und den Betrieb der zentralen IT-Infrastruktur des Uniklinikums.
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