The Biomedical signals and systems research group at the division of Signal processing and Biomedical engineering at the Department of Electrical Engineering is recruiting a qualified candidate for a PhD student position. We are an internationally renowned research group, focusing on research in the fields of Biomedical Engineering and Digital Health. This doctoral position is funded by the Kamprad Family Foundation (https://familjenkampradsstiftelse.se/in-english/) and is part of a strategic investment to develop and expand the Digital Health research and innovation activities at our department.
In this role you will join a research group that provides a stimulating, pleasant and flexible work environment for developing research and teaching, with a network reaching companies and health care representatives with special interest in Digital Health.
Background
The society is in the beginning of a large transformation of healthcare where more and more care, acute and chronic, will be provided in individuals' homes - supported by mobile care teams and Digital Health in many facets. Another strong trend is precision health, where the goal is to tailor care and treatments to each individual at every moment utilizing as much available data and information as possible - no matter their source.
The department and the research group
At the department of Electrical Engineering we value all our co-workers and we know that a variety of personalities and experiences makes the most creative workplaces. We therefore encourage applicants with any genders, backgrounds and abilities. Our overall ambition is to contribute to a sustainable future. We aim to create a positive impact on the development of society, both environmentally, socially and economically. Research and education are performed in the areas of Communication and Antenna systems , Systems and Control, Computer vision, Signal processing, Biomedical engineering and Electric Power Engineering. Our knowledge is of use everywhere where there is advanced technology with integrated electronics, no matter if it involves electricity, electrical signals, optical signals or microwaves. The department is a dynamic and international work environment with about 200 employees from more than 20 countries. We collaborate closely with both national and international academia, industry and medical researchers.
In our Digital Health group, we focus on sensor and data fusion in combination with clinical decision support tools using e.g. Artificial Intelligence (AI) to support informed clinical decisions and the transformation of healthcare. This advertised position will focus on care chains connecting home monitoring and acute incident detection with optimized prehospital care support, and more specifically fall incidents - a huge public health problem.
One focus area for the Digital Health research is Acute Support, Assessment and Prioritizing (ASAP), a concept for supporting acute incidents within remote/home care. One application for ASAP is prevention and supporting management of fall incidents in the home, which is a major problem afflicting tens of thousands of patients each year only in Sweden, striking patients with serious injures such as hip fractures and traumatic brain injury (TBI). A project has been created connected to ASAP for research and innovation to decrease the number of deaths and injuries due to falls in the home, named Autumn Leaves.
Project description
Health care is changing, and more care is being shifted towards home. One result is that medical devices and other equipment from different suppliers are placed in the home and generate individual-related information such as vital data, images, etc.
Typical of today's applications, such as Chronic Obstructive Pulmonary Disease (COPD) and heart failure, is that changes occur over relatively long periods of time - days/weeks. Therefore, procedures, processes and technical solutions are not designed to handle acute incidents where rapid response is crucial. At the same time, the possibility of detecting emergency conditions such as a fall with equipment being present in the home, and thus the possibility of acting quickly, increases. A prerequisite is that alarms and individual-related information from different suppliers and sources are provided to the prioritization and assessment process in a standardized way. This forms the foundation of the Autumn Leaves project, which gathers several important actors and companies that together have the possibility to develop a new concept to provide clinical benefits. Autumn Leaves will establish a system innovation model where quick access to individual information from sources like sensors in the home, patient record, social care, etc., together and with various decision support reduces time delays and increases the precision of prehospital care processes generated from emergency conditions in the home.
The project focus on falls, as this is a major and growing societal problem, and at the same time an application that clearly highlights the challenges and opportunities. Other conditions may include arrhythmias, cardiac arrest, epilepsy or diabetes. The core team is the multidisciplinary network that exists in prehospital research, development and innovation in Region Västra Götaland, reinforced by several companies and the City of Gothenburg. The project goal is to design and test a prototype ready for clinical testing.
For Autumn Leaves to become successful it all starts with effectively detecting a fall from a a multitude of sensors. The PhD student's research will involve sensor and data fusion utilization in health care systems for supporting clinical care processes, informed decision making and personalized healthcare. Methods will include the use of signal processing, sensor and data fusion, as well as AI/Machine Learning (ML) to develop and test a method for fall detection that uses various data sources as input, for example fall sensors mounted on the user, such as a smartwatch or other device worn on the wrist, and non-contact techniques, such as radar technology.
Main responsibilities
In this PhD student position you will play an important role in developing an ASAP/Autumn Leaves digital platform. Your research area will cover topics like multiple sensor information fusion, signal processing and interpretation utilizing AI/ML.
Specifically, you will contribute to the development of ASAP/Autumn Leaves through the following three activities:
1) Lay the theoretical foundation for the generic ASAP platform, i.e. define, evaluate and design how different sensors should work together.
2) Be involved in the hardware and software development for the ASAP platform.
3) Scientific dissemination via journal articles and conference publications.
Besides research, the position generally also includes teaching on Chalmers' undergraduate and master level corresponding to about 20 per cent of working hours. Chalmers started a new Master of Science in Biomedical Engineering programme 2020, and has a master programme in Biomedical Engineering since around 2007.
Contract terms
Full-time temporary employment. The position is limited to a maximum of five years.
Qualifications
To qualify for this position, you should have a master's level degree corresponding to at least 240 higher education credits in Engineering. You also need to have:
-Experience in signal processing
-Programming skills
-Interest in the above areas.
Experience from Biomedical Engineering/Digital Health is meritorious, as well as proficiency in theory and practice of sensor and data fusion, signal processing and AI/ML.
Good verbal and written communication skills in both Swedish and English are required, and good interpersonal skills are needed. If Swedish is not your native language, you will need to be able to develop Swedish skills for facilitating project communication with potential users. Chalmers offers Swedish courses.
Chalmers continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all activities at Chalmers.
We offer
Chalmers offers a cultivating and inspiring working environment in the dynamic city of Gothenburg.
At Chalmers, we seek to establish a good work/life balance. We want to provide you with the means to pick the best path possible in your pursuit of making a difference. Our ambitions in this area are reflected in the generous annual leave agreement, but also in many other areas, such as Chalmers' favourable arrangements for you as a parent. As an employer Chalmers actively strives towards providing equal opportunities for any gender.
Read more about working at Chalmers and our benefits for employees.
Application procedure
The application should be marked with Ref 20210241 and written in English. The application should be sent electronically and be attached as pdf-files, as below:
CV: (Please name the document: CV, Family name, Ref. number)
• CV
• Other, for example previous employments or leadership qualifications and positions of trust.
• Two references that we can contact.
Personal letter: (Please name the document as: Personal letter, Family name, Ref. number)
1-3 pages where you:
• Introduce yourself
• Describe your previous experience of relevance for the position (e.g. education, thesis work and, if applicable, any other research activities)
• Describe your future goals and future research focus
Other documents:
• Copies of bachelor and/or master’s thesis.
• Attested copies and transcripts of completed education, grades and other certificates, e.g. TOEFL test results.
Please use the button at the foot of the page to reach the application form. The files may be compressed (zipped).
Application deadline: 16 June, 2021
For questions, please contact:
Associate Professor Stefan Candefjord, Signal Processing and Biomedical Engineering (SPBME), stefan.candefjord@chalmers.se, +46 73-382 15 37
Professor of the practice Bengt Arne Sjöqvist, SPBME, bengt.arne.sjoqvist@chalmers.se, +46 70-787 77 97
Associate Professor and Head of Unit Biomedical Signals and Systems, Sabine Reinfeldt, SPBME, sabine.reinfeldt@chalmers.se, +46 31 772 80 63
*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***
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