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PHD Student in Medical Data Privacy
A wealth of sensitive data is continuously produced by body sensors, environmental sensors, bracelets, etc. These 'things' generate continuous streams of data, used in several domains. Prominently, health-based scenarios (e.g., in hospitals) rely on such streams to support the analysis and to diagnose illnesses. These streams of data typically need to be processed in a timely manner, potentially by exploiting and merging different streams. To reduce the costs of maintenance of large computing facilities required to handle these operations, it is desirable to outsource these computations to public cloud providers, which are typically untrusted. At the same time, they are source of highly sensitive and private data. Hence, the collection, storage and processing of such data require special care and offer challenging research opportunities. Users do not want to disclose unnecessary information but still to take advantage of the benefits of aggregate analysis. In this context, new EU regulations (General Data Protection Regulation 2016/679) will require and enforce proper handling of private data.
Recent advances in mass-market hardware, such as Intel SGX in the SkyLake CPUs, ARM’s TrustZone, or upcoming AMD's SME-SEV (generally referred to as “Trusted Execution Environments”) are offering breakthrough opportunities to provide uncompromised secure data handling for all the steps of a secure and privacy-preserving data processing pipeline. The thesis project will investigate the challenges of efficiently processing sensible data continuously streamed by sensors in a privacy-preserving fashion.
The work of the PhD student will revolve around the design and implementation of efficient techniques to exchange data between low-energy devices (the 'things') and public clouds in the context of vital sign monitoring. The candidate will investigate and propose novel techniques to combine streams of different natures (signals, images) leveraging the capabilities of public cloud providers and/or Trusted Execution Environments. Finally, she or he will have a fundamental role in the development and deployment of the prototype implementation respecting medical regulation and its evaluation.
The candidate will also work in close contact with R&D divisions at CSEM to drive the research toward practical industrial needs.
Your responsibility will also include to:
- Disseminate and report your results using international platforms
- Take active part in the activities of the MedTech group and interact with the PhD students in the European network.
- Master degree in Computer Science (or equivalent)
- Good written and spoken English
- Strong team-working abilities
- Enthusiastic, proactive and autonomous
- Excellent communication skills
- Former experience with mobile and/or wearable development (or willing to achieve it) is a plus.
CSEM offers a stimulating and multidisciplinary work environment with the opportunity to work with leading Swiss and international companies. You will have the opportunity to benefit from excellent social security conditions and to evolve within a multicultural company which clearly promotes an employee-driven culture.
We look forward to receiving your complete application file at firstname.lastname@example.org, mentioning ref. 'E251.2017-56' in the subject.
Preference will be given to professionals applying directly.