Application deadline: until the vacancy is filled.
Type of contract: Full-time.
Employment: 1 year, which is extended with until 4 years after positive evaluation at the end of the first year.
Starting date: As soon as possible.
We especially encourage applications by candidates from diverse groups; all are welcome in our team.
Personal Genomics is now becoming a reality, thanks to the steadily increasing availability of affordable sequencing technology. Despite the great promise of genomics for personal health and precision medicine, most institutions, as well as individuals, are hesitant to share genomic data. Principal reasons are the risk of unethical handling of the data, for example leading to higher insurance costs at the level of individuals. Hence, the build-up of trust for sharing this highly sensitive, identifiable personal information is critical, individually, nation-wide, and internationally.
Decentralization efforts such as Solid offer a solution to these problems. Solid allows users to be in full control over their own data, where applications need to ask them for permission to access their data, instead of the other way around. The combination of Solid and Genomics leads to “Genome Pods” where individuals can store their genome data inside a personal repository.
Considering the massive scale of genomic data, major challenges arise when querying over this data, especially when it is distributed across multiple Genome Pods. The goal of this PhD is to investigate and design highly performant query execution algorithms, so that query-driven applications can offer valuable insights into this genomic data.
Are you passionate about genomics, querying, the Web, and interested in working on decentralization? Join our team to work on the next phase of the Web! Under the supervision of a.o. dr. Gokhan Ertaylan, expert in genomics, and dr. Ruben Taelman, expert in querying over decentralized knowledge graphs, can contribute to bringing personal genomics to healthcare practice.
Read more about our work on personal data ecosystem building and querying over decentralized knowledge graphs here:
- Degree: Master’s degree in Computer Science, Engineering, Informatics, ICT or related field
- Advanced programming skills in at least 1 major programming language
- Passionate about Web technology
- It is a plus if you have experience with genomics or health data standards
- Fluent in English, spoken and written
- Self-directed and able to perform independent work
- Enthusiastic about working in a research environment
This is a joint PhD position that spans the Knowledge on Web-Scale team at Ghent University, and the Precision Health Group at VITO.
The Knowledge on Web-Scale team at Ghent University – imec is renowned for
its creative research on Knowledge Graphs on the Web.
We apply these techniques on open data, shared data, and personal data in a wide range of application domains
such as mobility, digital heritage, scholarly communication, sensor data, governmental base registries, building data,
e-health, and logistics.
KNoWS is part of IDLab within Ghent University,
a top-100 university worldwide, located in the heart of Belgium.
IDLab is a core research group of imec,
a world-leading research and innovation hub in digital technologies and nanoelectronics.
IDLab employs over 300 researchers working on fundamental and applied research on data science and internet technology.
VITO’s Precision Health Group (PHG) has the vision of creating a personalized healthcare and clinical landscape
empowered by Digital (Virtual) Twins technologies using AI and data driven methodologies.
We focus on developing data driven applications for healthcare & clinical practice.
Primary focus is the integration of personal health data at various levels (genomics, proteomics, clinical biochemistry,
e-health records and real-world data) to enable precision health applications.
PHG is situated in the VITO Sustainable Health unit and is working with an international and
multi-disciplinary team supporting personal health data sharing initiatives, diagnostic research and
their application in clinical & healthcare practice.
Our research towards creating personal health data vaults for hosting various sources of
personal health data is geared towards enabling Digital Twins at the national as well as at the European level.
We are part of the consortium of European initiative for Digital Twins in Healthcare
as well as other major Horizon EU projects in developing best practices for healthcare and clinical software in
EU regulatory settings.
We are highly committed to making translational research data FAIR (Findable, Accessible, Interoperable and Useable),
while developing tools and resources to ensure the transparency, robustness, FAIRness and accountability of
proposed methodologies and applications.
You receive the opportunity to perform full-time research in a highly international and friendly working environment, with a competitive salary. Grounded in fundamental academic research, as a PhD candidate you will also participate in collaborative research with industrial and academic partners in Flanders and on a wider geographic scale in new and ongoing projects. You will publish your research results at major international conferences and in journal papers.