Postdoc position in the field of medical data/neurorehabilitation
100%, Zurich, fixed-term
This position is open for a postdoctoral researcher in the field of Medical Data Engineering and Modelling with Multimodal Sensor Acquisition. The focus of this work will be on achieving an automated data acquisition and information processing system for neurorehabilitation in Switzerland.
This is an exciting project where you will collaborate with researchers and clinical informatics teams to explore efficient methods for integration of various health data sources. These sources will include health databases, hospital data, and multimodal sensor data. The system goals are continuous, resilient, and compliant data aggregation into a central data warehouse. Both structured and unstructured data will be aggregated, quality controlled, and prepared to make them actionable for research questions concerning the optimisation of neurorehabilitation treatment. This project is part of the Innosuisse SwissNeuroRehab flagship project, which encompasses clinical and research partners throughout Switzerland.
You will join and profit from a large interdisciplinary network and will be involved in core activities in the field hosted by the ETH competence center for Rehabilitation Engineering and Science (RESC: www.resc.ethz.ch). Within this group, you will work closely with the Cereneo Foundation, a non-profit research foundation that specializes in developing and deploying digital data collection tools and health interventions into clinical practice (www.cereneo.foundation).
The position is fully funded for 2 years: ideally starting in July 2023.
The position will be supervised:
- At ETH Zurich by Dr Diego Paez, SCAI Lab, and Prof. Robert Riener’s research group, the leading chair of RESC.
- At the University of Zürich by Dr Chris Awai, as part of Prof. Andreas Luft’s research team.
Project background
“SwissNeuroRehab”, an Innosuisse flagship project, aims to develop a new model of neurorehabilitation which address the whole continuum of care - from in-patient rehabilitation to decentralized home therapy. The blend of conventional therapy approaches augmented with digital tools and completely novel technologies for home rehabilitation affords an opportunity to provide truly personalized care to patients and people living with disabilities. The flagship project unites the major academic, clinical, and industrial players in Switzerland towards this common goal. ETH Zurich and the University of Zurich are part of this team and are offering in this context a shared position for a postdoctoral researcher.
Job description
Your main responsibilities will include investigating data engineering for digital pathways of neurorehabilitation, creating interoperable and user-friendly clinical information warehousing solutions with envisioned big data analysis. These solutions must be scalable, secure, and compliant with ethical and regulatory requirements. Additionally, you will develop user-facing digital data acquisition tools and rehabilitation technology that integrate with the centralized warehousing solution in electronic health record (EHR) systems. It is crucial that your solution offers flexibility and high performance for large-scale analyses.
Once completed, the solution will be extended to remote rehabilitation settings, enabling comprehensive data analysis across the entire continuum of care.
In summary, as the first hire for this team, you will contribute to groundbreaking research, collaborate with interdisciplinary teams, and create innovative solutions to improve healthcare outcomes.
Your profile
You have outstanding practical experience in data engineering and big data with a PhD degree in Computer Science or related subject.
- Experience in databases and recent data interoperability frameworks (e.g. FHIR, OMOP)
- Proficiency in programming, preferably in Python and Java, SQL is a must
- Strong analytical, mathematical, and algorithmic capabilities
- Proven record of leading interdisciplinary projects
- Demonstrated experience in full-stack development
- Proven track record in big data processing and deploying machine learning models into production (preferred)
- Experience in digital health, mobile health, and biomedical sensor data acquisition (preferred)
- Experience with clinical/human trials will be considered an asset
- Very good knowledge of English, German/French/Italian is a plus
- Project management skills and the ability to supervise master theses and internship students
Your workplace
Your workplace
We offer
You will join a team of clinical and research scientists in the task of improving rehabilitation systems through physiological and clinical data systems design and analysis. The focus of this work will bring you close to intelligent health management while exploring various health data frameworks. You will experience multimodal data from robotic rehabilitation, digital data collection, general clinical practice, and detailed clinical studies focusing on interoperability, data transfer, and standardization among multiple clinical systems and devices.
As part of the position, we will enable you to interact and gather deep experience working closely with our wide range of collaborators, including the clinical data warehouse (CTC, USZ), digital trial intervention center (dTIP, ETH), SCAI Lab (SPZ Nottwil), Sense Innovation Research Center (HES-SO Valais), cereneo Foundation. A versatile and challenging task at the interface of clinic and academia awaits you.
We offer a full-time research position (100%) with a competitive salary in accordance with ETH standards.
The work location is flexible and would rotate between ETH Zurich, SPZ Nottwil and Cereneo Foundation Vitznau with flexibility for remote work.
We value diversity
Curious? So are we.
We look forward to receiving your online application with the following documents:
- Curriculum vitae
- Cover letter describing your motivation and research experience (max 1 page)
- Copy of one relevant journal publication
- Name and contact details of two referees
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Questions regarding the position should be directed to Chris Awai chris.awai@cereneo.foundation (no applications).
About ETH Zürich
Curious? So are we.
We look forward to receiving your online application with the following documents:
- Curriculum vitae
- Cover letter describing your motivation and research experience (max 1 page)
- Copy of one relevant journal publication
- Name and contact details of two referees
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Questions regarding the position should be directed to Chris Awai chris.awai@cereneo.foundation (no applications).