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The Digital Sports Group of the Pattern Recognition Lab (Friedrich-Alexander-Universität Erlangen-Nürnberg, FAU) currently invites applications for the following fully funded 36 month PhD position in Computer Science in Sports / Biomedical Engineering:
"Individualized, Sensor-based Diagnostics and Therapy Monitoring for Mobility Impairment Analysis"
Background:
Analysis of mobility impairment from biomedical (motion) sensors is an emerging topic in computer science and biomedical engineering. This PhD position is funded through an interdisciplinary project co-supervised at the Faculty of Engineering and the Faculty of Medicine at the FAU. The focus is to develop state-of-the-art wearable computing, biomedical signal analysis and machine learning systems to assess diagnostic validity and therapy success in neurologic and musculoskeletal movement disorders. The sensor-based movement information will be mirrored by modern high-tech diagnostic approaches (molecular imaging, MRI, biomechanical movement analysis) to combine continuous detection of mobility impairment with state-of-the-art high-end diagnostic assessment. The project aims at developing sensor-based signal analysis to allow an individualized, quantitative, and qualitative assessment of mobility impairment symptoms. An interdisciplinary team of scientists conducts the project, and the successful candidate is expected to be an avid team worker.
The FAU is one of the largest universities in Germany. With its five faculties, FAU offers a scope of subjects ranging from the Humanities to Law and Economics as well as Sciences, Medicine and Engineering. The FAU’s mission statement “Advance through Networks” reflects the close collaboration between the single disciplines. The Pattern Recognition Lab at the FAU develops signal processing and pattern recognition algorithms for biomedical signal analysis. Its Digital Sports Group (Prof. B. Eskofier) specifically works on motion and biosignal analysis. We focus on mobile data from wearable computing systems that have a wide range of applications. Detailed information on ongoing projects is available on our website, via our publications and upon request.
Requirements:
Candidates for this position should have a master or comparable degree in Computer Science or a related discipline (Electrical Engineering, Biomedical Engineering, …). The ideal candidate blends technical expertise in hardware and software of wearable computing systems with an interest in sports science, biomechanics, and medicine as an application area. The candidate should also be enthusiastic about building a research program including project proposals and (limited) participation in teaching at the intersection of computer science and biomedical engineering applications.
Program details and contact for application/questions:
The project start date is September 1, 2014. Funding is available for at least 36 months, an extension is possible based on the project evaluation. Prospective applicants should apply with a cover letter and academic CV. Applications will be accepted until the position is filled.
For informal inquiries about the position please contact Prof. B. Eskofier (eskofier@cs.fau.de), head of the Digital Sports Group at the Pattern Recognition Lab. Further details are online at:
http://www5.cs.fau.de/open-positions/.
Prof. Bjoern Eskofier, Ph.D.
Assistant professor for Computer Science in Sports
Endowed professorship of the adidas AG
Digital Sports Group
Pattern Recognition Lab (Computer Science 5)
Department of Computer Science
Friedrich-Alexander-University Erlangen-Nuremberg
Haberstr. 2, 91058 Erlangen, Germany
I-net: http://www5.cs.fau.de
Phone: +49 9131 85-27297
Email: eskofier@cs.fau.de
"Individualized, Sensor-based Diagnostics and Therapy Monitoring for Mobility Impairment Analysis"
Background:
Analysis of mobility impairment from biomedical (motion) sensors is an emerging topic in computer science and biomedical engineering. This PhD position is funded through an interdisciplinary project co-supervised at the Faculty of Engineering and the Faculty of Medicine at the FAU. The focus is to develop state-of-the-art wearable computing, biomedical signal analysis and machine learning systems to assess diagnostic validity and therapy success in neurologic and musculoskeletal movement disorders. The sensor-based movement information will be mirrored by modern high-tech diagnostic approaches (molecular imaging, MRI, biomechanical movement analysis) to combine continuous detection of mobility impairment with state-of-the-art high-end diagnostic assessment. The project aims at developing sensor-based signal analysis to allow an individualized, quantitative, and qualitative assessment of mobility impairment symptoms. An interdisciplinary team of scientists conducts the project, and the successful candidate is expected to be an avid team worker.
The FAU is one of the largest universities in Germany. With its five faculties, FAU offers a scope of subjects ranging from the Humanities to Law and Economics as well as Sciences, Medicine and Engineering. The FAU’s mission statement “Advance through Networks” reflects the close collaboration between the single disciplines. The Pattern Recognition Lab at the FAU develops signal processing and pattern recognition algorithms for biomedical signal analysis. Its Digital Sports Group (Prof. B. Eskofier) specifically works on motion and biosignal analysis. We focus on mobile data from wearable computing systems that have a wide range of applications. Detailed information on ongoing projects is available on our website, via our publications and upon request.
Requirements:
Candidates for this position should have a master or comparable degree in Computer Science or a related discipline (Electrical Engineering, Biomedical Engineering, …). The ideal candidate blends technical expertise in hardware and software of wearable computing systems with an interest in sports science, biomechanics, and medicine as an application area. The candidate should also be enthusiastic about building a research program including project proposals and (limited) participation in teaching at the intersection of computer science and biomedical engineering applications.
Program details and contact for application/questions:
The project start date is September 1, 2014. Funding is available for at least 36 months, an extension is possible based on the project evaluation. Prospective applicants should apply with a cover letter and academic CV. Applications will be accepted until the position is filled.
For informal inquiries about the position please contact Prof. B. Eskofier (eskofier@cs.fau.de), head of the Digital Sports Group at the Pattern Recognition Lab. Further details are online at:
http://www5.cs.fau.de/open-positions/.
Prof. Bjoern Eskofier, Ph.D.
Assistant professor for Computer Science in Sports
Endowed professorship of the adidas AG
Digital Sports Group
Pattern Recognition Lab (Computer Science 5)
Department of Computer Science
Friedrich-Alexander-University Erlangen-Nuremberg
Haberstr. 2, 91058 Erlangen, Germany
I-net: http://www5.cs.fau.de
Phone: +49 9131 85-27297
Email: eskofier@cs.fau.de