ESR Vacancies

15 PhD positions are available for highly motivated Early Stage Researcher (ESR) as part of the visuAAL project.

See below the details for each of these positions: job and project descriptions, requirements, salary, application and selection procedures, additional requirements...

Please, read the call for applications for a specific project (below) before applying.

Deadline: 30th November 2020 Until all the positions are filled

NOTE: During the application process, applicants are able to select multiple positions in case they were interested in several of the research projects.

Eligibility criteria

  • Applicants must hold a master’s degree (or equivalent) relevant to the project(s) they apply for. Please, check the degrees that are relevant for each project in the call for applications below.
  • Applicants should not have been awarded a PhD degree
  • At the time of recruitment, applicants must have less than four (full time equivalent) years of experience within a research career (measured from the date when the applicant obtained the first degree entitling him/her to embark on a doctorate, even if a doctorate was never started or envisaged)
  • Applicants can have any nationality
  • Applicants must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting institution for more than 12 months in the 3 years immediately before the recruitment date
  • Proficiency in written and spoken English
  • Additional criteria can apply for each specific research project (see the details about each project below)

IMPORTANT NOTE: Each project has its own call for applications (below) specifying the relevant master's degree and additional criteria. Please, confirm that you fulfil those requirements before applying for a particular project. We have detected that some applicants apply for several projects: one that requires a degree in Law, another one that requires a degree in Psychology, and another one that requires a degree in Computer Science. It is highly unlikely that an applicant could fulfil all those requirements.

Apply now

 

 

 

  Research Project 1  

Perceptions of personal privacy in health monitoring technologies (in different users)

The aim of this doctoral thesis is to identify differently perceived dimensions and degrees of privacy, taking user group-specific needs and requirements for lifelogging technologies in diverse contexts into account. Covering a broad range of lifelogging technologies (e.g., video-based, audio-based, sensor-based), perception of privacy should be analysed technology-specifically. The focused target groups are users of the whole life span, but the thesis will specifically target older and frail persons, who have experiences with chronic illnesses and care. The here resulting gradations of privacy can be elaborated and subsequently appropriately concerned by respective stakeholders. 

Host institution: RWTH Aachen University,  Germany

Please, read the call for applications for this project before applying.

For more information about this project, please contact Prof Martina Ziefle 

Apply now

 

  Research Project 2  

(Dis)Trust in medical technologies and medical support considering (severe) health decisions

Trust as a major component of the acceptance of medical technologies is essential. Especially in severe health- and life-end-decisions, socio-ethical perspectives on lifelogging and medical technology are of paramount impact. Thereby, trust in technologies and decisions of medical personnel are of utmost importance for people who need assistance and care. Yet, trust concepts prevailing are concentrating on different usage contexts and lack of understanding which factors need to be considered in severe illness and under vital conditions. This thesis examines the extent to which trust in technology and medical support impacts technology acceptance and decisions in (severe) health situations.

Host institution: RWTH Aachen University,  Germany

Please, read the call for applications for this project before applying.

For more information about this project, please contact Prof Martina Ziefle 

Apply now

 

  Research Project 3  

Acceptance of artificial intelligence in health-related contexts​

This thesis focuses on the perception and acceptance of intelligent solutions for supporting, on the one hand, people who suffer from chronic diseases as well as medical staff, on the other hand. Required and desired functions of the technologies will be explored depending on the respective context and user group. In addition for the investigation of acceptance, perceived benefits, perceived barriers, and usage conditions are examined for a broad spectrum of health settings.

Host institution: RWTH Aachen University,  Germany

Please, read the call for applications for this project before applying.

For more information about this project, please contact Prof Martina Ziefle 

Apply now

 

  Research Project 4  

Video-based AAL technologies and colliding legal frameworks

While the emergence of AAL technologies within the context of healthcare present incredible opportunities to improve the life quality of the frail and sick, these technologies pose significant legal issues. These technologies require coherent legal regulation in order to ensure, among other things, the safety of the device and the privacy of the individual using it. Taking a global perspective, this project will explore the current legal framework governing video-based AAL technologies and involve an in-depth interpretation and systematization of the positive law related to this emerging field. While the bulk of the work will involve a deep dependence on traditional legal sources, reliance on materials gathered in the domain of computer science and a translation of these materials into a legal context will be necessary.

Host institution: Stockholm University,  Sweden

Please, read the call for applications for this project before applying.

For more information about this project, please contact Prof Peter Wahlgren and Dr Liane Colonna

Apply now

 

  Research Project 5  

Video-based AAL technologies and balancing of interests

An aspect that is necessary to take into account, when introducing new technologies into society, is that there are bound to be multiple interests at stake, which potentially come into conflict with each other, particularly from a legal perspective. For example, under the General Data Protection Regulation (GDPR), an individual is able to gain access to the logic behind automated decisions that affect him or her, yet only to the extent that it does not interfere with any intellectual property rights to that technology (see Article 22 and Recital 63 GDPR). Another illustration concerns AAL technologies that have the potential to erode an individual’s privacy rights while at the same time bring great benefits to society in terms of the reduction of treatment costs. In short, this thesis will examine how the law should balance interests within the context of Video-based AAL technologies.

Host institution: Stockholm University,  Sweden

Please, read the call for applications for this project before applying.

For more information about this project, please contact Prof Peter Wahlgren and Dr Liane Colonna

Apply now

 

  Research Project 6  

“Digital twins” as a way to help ensure legal compliance of video-based AAL technologies

The General Data Protection Regulation (GDPR) offers strong protection for the individuals’ integrity. At the same time, video-based AAL technologies present serious privacy concerns that threaten the long-term sustainability of these products. One way to speed up the implementation of important research within the context of AAL technologies is to simulate data in digital twins [here, agent based modelling should also be a powerful tool], thus helping to solve key future issues without compromising individual integrity. Investigating opportunities to carry out important research without having to use personal data, but instead data on "computer generated agents" or other simulations is the focus of this project.

Host institution: Stockholm University,  Sweden

Please, read the call for applications for this project before applying.

For more information about this project, please contact Prof Peter Wahlgren and Dr Liane Colonna

Apply now

 

  Research Project 7  

Use of camera systems to support home based multiple chronic disease (multimorbidity) self-management

Self-management is a critical component of chronic disease management and can include activities, such undertaking daily care activities, managing medication, and proactively linking in with one’s care network (informal carers, formal carers and healthcare professionals). The rise of digital health technologies (mobile applications/phones, sensor-based devices, cameras) to assist health and well-being management of chronic diseases offers potential support for people to better manage their diseases in collaboration with their care network. Camera systems (both home-based and wearable) may be used to provide rich contextual data and insight into everyday activities to better understand the complexity of multiple disease (multimorbidity) management. This information can then be a) used to better guide self-management activities and b) shared with an individual’s care network to help develop truly collaborative goal-based interventions to support self-management. Use of cameras to better understand and augment self-management by people with multimorbidity has yet to be fully explored. This PhD will aim to understand and define the use of camera-based technologies for older adults living at home with multiple chronic health conditions (e.g. multimorbidity). Particular emphasis will be placed on understanding the factors that impact the relationship between individuals with multimorbidity and their care network.

Host institution: Trinity College Dublin,  Ireland

Please, read the call for applications for this project before applying.

For more information about this project, please contact Dr John Dinsmore

Apply now

 

  Research Project 8  

Application of behavioural change theory to the design, development and implementation of camera systems to support home-based multiple chronic disease (multimorbidity) self-management

Understanding of the application of behavioural change theory to the design, development and implementation (including potential privacy and ethical concerns) of camera systems to support multiple disease self-management (multimorbidity) to our knowledge has not yet been addressed in research literature. The objectives of this PhD Project will be to 1) conduct a systematic review of how behavioural change theory has been used to inform the development and use of visual/video solutions for home based chronic disease management. 2) Use the Behavioural Change Wheel (BCW) framework to determine behavioural targets, functions and techniques to enhance our understanding of how best to facilitate adoption of camera based interventions in the home environment for multimorbidity self-management.

Host institution: Trinity College Dublin,  Ireland

Please, read the call for applications for this project before applying.

For more information about this project, please contact Dr John Dinsmore

Apply now

 

  Research Project 9  

Personalisation of self-management education/training for individuals with multiple chronic health conditions (multimorbidity) using visual based data

The aim of this PhD is to explore machine learning or artificial intelligence (AI) approaches to the use of visual based data to aid personalisation of education and training for individuals living with multimorbidity. Research will involve defining user and behaviour change models to facilitate appropriate AI approaches to tailor educational and training interventions, based on an individual’s self-management needs as captured from camera based systems in the home. The PhD will also focus on understanding data protection, ethical and privacy concerns in relation to the use of AI approaches for using visual data to inform an individual’s education and training in relation to their self-management.

Host institution: Trinity College Dublin,  Ireland

Please, read the call for applications for this project before applying.

For more information about this project, please contact Dr John Dinsmore

Apply now

 

  Research Project 10  

Behaviour modelling and life logging

Lifelogging is a recent ICT technology that uses wearable sensors (e.g. cameras, trackers, wearable sensors) to capture, store, process and retrieve the different situations, states and context of an individual in daily life. Using a wearable camera that automatically takes 3 images per minute provides about 2000 pictures at the end of each day that can illustrate in detail which activities the person wearing the camera has done - e.g. how (s)he eats, what places (s)he visited, with whom (s)he interacted, what events (s)he attended, etc. In this way, the topic of this thesis is lifelogging in order to create personalized tools and services to monitor, store and process the behavioural skills, nutrition patterns, social environment, context and proper physical activities during long periods in an objective way.

Host institution: TU Wien,  Austria

Please, read the call for applications for this project before applying.

For more information about this project, please contact Dr Martin Kampel

Apply now

 

  Research Project 11  

Algorithmic governance for active assisted living

Algorithmic decision making became enmeshed into daily life. In active assisted living data is analysed and interpreted with the intention to support people in various ways: recognizing behaviour, events, emotions, needs; creating ambient intelligence; predicting activities and proposing treatment strategies. Machine learning as prerequisite of intelligence is applied. Taking into account recent success, it can be claimed, that not only a set of specific algorithms but also a lot of example data is needed to run the learning methods. And usually those building the algorithms are not trained in law or the social sciences, while experts in discrimination law do not know how to audit modern machine learning algorithms. Further complicating matters is that even experts in computer science and mathematics often struggle with interpreting the output of many modern machine learning algorithms. Unsurprisingly assessing and guaranteeing fairness and transparency in machine learning is a wide open research and that is the topic of the PhD proposal.

Host institution: TU Wien,  Austria

Please, read the call for applications for this project before applying.

For more information about this project, please contact Dr Martin Kampel

Apply now

 

  Research Project 12  

AI for dementia care

Although the progress and severity of dementia varies depending on the underlying cause (e.g. Alzheimer´s disease) there are common symptoms between the manifestations. These symptoms include personality changes, which manifests itself in becoming subdued or withdrawn. By using machine learning in long-term emotional analysis, it should be possible to recognize patterns and thus determine personality changes. In order to assign the person´s mood correctly, it is necessary that the algorithms treat the emotions context aware. This means that the current situation and environment of the person is detected (e.g. by sensors or smartphone) which allows to determine whether certain emotions are only felt in company or alone.

Host institution: TU Wien,  Austria

Please, read the call for applications for this project before applying.

For more information about this project, please contact Dr Martin Kampel

Apply now

 

  Research Project 13  

Privacy preservation in video-based AAL applications

Visual data exposes a lot of information about individuals appearing on images and videos. Individuals may want to conceal all of this data, but in this case, the remaining information would be useless for the AAL services that build upon it. Therefore, there is a need to establish a trade-off between privacy and intelligibility of the images. This project will advance in a privacy-by-context approach, in which different visualisations are produced depending on the context in which images or videos are captured: Identity, appearance, location, ongoing activity of the subject being monitored; event triggered; identity and access rights of the observer; closeness between observer and monitored subject… While these privacy-by-context approach has been successfully employed using RGB-D cameras, it has been difficult to address privacy preservation using regular RGB cameras either located in the environment (preferably on the ceiling) or worn by the user. Therefore, this project will investigate visualisations methods to conceal visual privacy in applications and services for older and frail people that employ RGB cameras.

Host institution: Universidad de Alicante,  Spain

Please, read the call for applications for this project before applying.

For more information about this project, please contact Dr Francisco Florez-Revuelta

Apply now

 

  Research Project 14  

Context recognition for the application of visual privacy

Most works conceal people’s visual privacy by using blurring or pixelating effects to modify an image. In a privacy-by-context approach, a level-based visualisation scheme to protect privacy is proposed. Each level establishes the way in which the video images are modified and displayed and, therefore, the provided protection degree. In this scheme, the appropriate level is dynamically selected according to the context, therefore modifying a non-protected image before it is displayed. The context has to provide enough information in order to empower people to adapt privacy to their preferences, in such a way that they can decide by whom, how and when they can be watched. The context is modelled by different variables: (i) the observer; (ii) the identity of the person (to retrieve the privacy profile); (iii) the closeness between the person and observer (e.g., relative, doctor or acquaintance); (iv) appearance (dressed?); (v) location (e.g., kitchen); and (vi) ongoing activity or detected event (e.g., cooking, watching TV, fall). Therefore, an accurate recognition of the context is paramount to provide the appropriate privacy level. This project will investigate techniques to recognise accurately these variables and it will validate them under different use case scenarios.

Host institution: Universidad de Alicante,  Spain

Please, read the call for applications for this project before applying.

For more information about this project, please contact Dr Francisco Florez-Revuelta

Apply now

 

  Research Project 15  

Perceptions of personal safety and privacy in frail elderly, disabled people and their caregivers in the context of video-based lifelogging technologies

The aim of this thesis is to analyse the acceptance of AAL (lifelogging) technologies, essentially the monitoring with video cameras located in public and private spaces, by their potential users. Including as a potential user, both the frail elderly patients and people with disabilities and with needs of aid, and their caregivers, formal or informal. Different types of cameras, locations, and type of information will be considered as well as benefits (for example, medical safety) and related barriers (for example, the threat to their privacy).

Host institution: Universidad de Alicante,  Spain

Please, read the call for applications for this project before applying.

For more information about this project, please contact Dr Francisco Florez-Revuelta

Apply now