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<tt>POSITION: Research Associate in the field Machine Learning and
AI for Mechatronic Systems (SAIL subproject A.4: Care bed
robotics)<br>
LOCATION: Bielefeld University of Applied Sciences, Bielefeld,
Germany<br>
<br>
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<br>
With more than 10,000 students, Bielefeld University of Applied
Sciences is the largest university of applied sciences in East
Westphalia-Lippe (OWL). Based in Bielefeld, Minden and Gütersloh,
it has an excellent network not only in the OWL region, but also
nationally and internationally through diverse contacts,
partnerships and cooperations in science, economy, politics and
culture. The Faculties of Design, Minden Campus, Engineering and
Mathematics, Social Sciences, Business and Health strive for high
quality in teaching and research.<br>
<br>
Within the framework of the funding announcement “Networks 2021”
(Netzwerke 2021) by the Ministry of Culture and Science of the
State of North Rhine-Westphalia (MKW NRW) for the sponsored
project “SustAInable Life-cycle of Intelligent Socio-Technical
Systems” (SAIL), the Faculty of Engineering and Mathematics seeks
to employ a<br>
<br>
*** Research Associate in the field Machine Learning and AI for
Mechatronic Systems (SAIL subproject A.4: Care bed robotics) *** <br>
<br>
to start immediately. The full-time position is fixed-term until
31 July 2026. Depending on individual qualification and tasks,
remuneration will be up to salary group 13 TV-L (collective
agreement of the federal state.) A cooperative doctorate can be
pursued as part of the employment. Your workplace will be on
Bielefeld Campus.<br>
<br>
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Current systems that contain AI technology are primarily targeted
at the introductory phase, a core component of which is training
and customising AI models based on given sample data. The new SAIL
research network is intended to develop the foundations for a
sustainable design of AI components. The aim is to ensure that AI
systems work transparently, safely and reliably throughout their
entire product life cycle. In addition to Bielefeld University of
Applied Sciences, this interdisciplinary network comprises
Bielefeld University, Paderborn University and OWL University of
Applied Sciences and Arts.<br>
<br>
The project addresses fundamental research in the field of AI, its
implications from the perspective of the humanities and social
sciences, as well as concrete fields of application in Industry
4.0 and Intelligent Healthcare.<br>
<br>
There are various life situations in which people depend on
nursing care in a care bed during the course of or as a result of
an illness. Care beds, especially intensive care beds with a large
number of actuators, can be seen as robots themselves, taking care
of the users in them, e.g. by carrying out repositioning movements
to prevent pressure ulcers. In this subproject, an intensive care
bed is available, which has RGB, depth image and infrared cameras
as well as sensors for pressure distribution measurements on the
bedding surface and whose drives are computer-controlled. The
subproject begins with a fusion of the sensor data and uses
ML-based modelling approaches to determine/estimate non-directly
measurable process variables and patient characteristics from a
subset of the sensors (e.g. estimation of the lying pressure
distribution without pressure distribution measurement as a basis
for repositioning movements of the bed). The AI questions that
follow concern, for example, model individualisation, natural
modes of interaction and adaptivity.<br>
<br>
Tasks and responsibilities: <br>
- Independent project coordination and implementation within the
research network<br>
- Conduct of independent research activities within the framework
of the research project:<br>
➜ Identification and definition of requirements for the workflow,
the algorithms to be used and the underlying mechatronic
infrastructure<br>
➜ Design and conduct of measurement campaigns with test subjects<br>
➜ Research into hybrid models as well as AI and ML methods for
robust and interpretable prediction of process variables and
patient characteristics/body parameters<br>
➜ Research into approaches to the continuous adaptation of hybrid
models<br>
➜ Implementation of ML approaches for controlling the intensive
care bed demonstrator<br>
➜ Implementation of the methods on the demonstrator<br>
➜ Generalisation of the developed approaches<br>
➜ Application and transfer of research results<br>
- Instruction and guidance of student and research assistants<br>
- Knowledge transfer/publications/conference presentations<br>
- Support of project lead in other project activities within the
scope of SAIL<br>
- Implementation of creative ideas in the research network as well
as interdisciplinary work<br>
<br>
You will perform these tasks independently in coordination with
Professor Dr. rer. nat. Axel Schneider. In addition, you will work
in an interdisciplinary team consisting of the research associates
of the other universities and other professors.<br>
<br>
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Requirements: <br>
- Master of Science/Engineering from a university or university of
applied sciences in electrical engineering, computer science,
biomechatronics or related subjects<br>
- In-depth expertise in the collection, processing and algorithmic
evaluation of (image) sensor data<br>
- Expertise in machine learning, embedded and robotic systems<br>
- First practical experience with the methods and toolboxes of
machine learning<br>
- Very good programming skills (Python, C(++), MATLAB/Simulink,
etc.)<br>
- Excellent conceptual and analytical thinking and action<br>
- Independent and autonomous way of working<br>
- Outstanding intellectual capacity<br>
- Experience in writing academic texts and presenting scientific
work results<br>
- Very good knowledge of written and oral German and English<br>
- Excellent team spirit and communication skills, confident
demeanour<br>
<br>
Candidates are further required to make sure that their fixed-term
employment does not exceed the limits prescribed by the
Wissenschaftszeitvertragsgesetz due to previous employments.<br>
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The ideal candidate should also bring:<br>
- Experience in project coordination<br>
- Experience in research activities, in the preparation of
scientific reports and publications or activities as a student or
research assistant<br>
- Experience in handling hardware components (e.g. installation
and integration of sensors)<br>
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Benefits: <br>
- Mobile work possible<br>
- Opportunities for participation in qualification programmes<br>
- Support offers for publications and patents<br>
- University daycare facility “EffHa” and holiday care for
schoolchildren on Bielefeld Campus<br>
- 6 faculties with diverse partnerships and research
collaborations in one of the most economically powerful regions in
Germany<br>
- Good accessibility by public transport<br>
- Participation in the university sports programme from Bielefeld
University<br>
<br>
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<br>
Bielefeld University of Applied Sciences has received multiple
awards for its successes in promoting equal opportunities and has
been certified as a family-friendly university. Therefore, women
are particularly welcome to apply, especially in the field of
research and in technology, IT and crafts.<br>
Applications from women will be given preference in case of equal
suitability, skills and professional performance, unless reasons
concerning the person of another applicant predominate.<br>
<br>
Persons with severe disabilities are encouraged to apply, too.
Subject to other applicable laws, severely disabled applicants
with equivalent qualifications will be given preferential
consideration.<br>
<br>
Please find more detailed information on the SAIL subprojects at:
<a class="moz-txt-link-freetext" href="https://jaii.eu/sail">https://jaii.eu/sail</a>. Multiple applications for other subprojects
in the network are expressly welcome. In this case, please include
the reference numbers of the respective subprojects in your
application.<br>
<br>
If you have any questions relating to the content of the position
we offer, please contact Prof. Dr. rer. nat. Axel Schneider via
e-mail at axel.schneider[AT]fh-bielefeld.de.<br>
<br>
** Are you interested? Please apply online only by 6 October 2022,
stating the reference number 03231. **<br>
<br>
Application link:
<a class="moz-txt-link-freetext" href="https://app.fh-bielefeld.de/qisserver/rds?state=change&type=3&nextdir=sva/bwmsas&subdir=sva/bwm&moduleParameter=bwmSearchResult&next=TableSelect.vm&P_start=0&P_anzahl=100&navigationPosition=qissvaCareer%2Csvabwmstellenuebersicht&breadcrumb=sva_bwm_stellenuebersicht&topitem=qissvaCareer&subitem=svabwmstellenuebersicht">https://app.fh-bielefeld.de/qisserver/rds?state=change&type=3&nextdir=sva/bwmsas&subdir=sva/bwm&moduleParameter=bwmSearchResult&next=TableSelect.vm&P_start=0&P_anzahl=100&navigationPosition=qissvaCareer%2Csvabwmstellenuebersicht&breadcrumb=sva_bwm_stellenuebersicht&topitem=qissvaCareer&subitem=svabwmstellenuebersicht</a><br>
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