Doctoral Position in Digital Health Technologies for Real-Time Processing of Optical Brain Imaging Signals

26 Jan 2024
Job Information

Organisation/Company

ETH Zürich

Research Field

Engineering » Biomedical engineering
Engineering » Electrical engineering
Computer science » Other
Engineering » Other
Computer science » Programming

Researcher Profile

First Stage Researcher (R1)

Country

Switzerland

Application Deadline

24 Apr 2024 - 21:59 (UTC)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

41

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Doctoral Position in Digital Health Technologies for Real-Time Processing of Optical Brain Imaging Signals

The Rehabilitation Engineering Lab (RELab) at the Department of Health Sciences and Technology at ETH Zurich is an interdisciplinary group with competencies in mechanical and electrical engineering, movement science, neurorehabilitation and neuroscience. The RELab uses robotics, wearable sensor technologies, and non-invasive neuroimaging to explore, assess and restore sensorimotor function in persons with neurological injury, to promote sensorimotor recovery and independence.

Together with the Cereneo Center for Neurology and Neurorehabilitation we are developing a novel, neuroimaging-guided therapy method to support point-of-care treatments in stroke rehabilitation, aiming to seamlessly include the brain in the neurorehabilitation therapy.

Project background

Stroke is a leading cause of long-term disability worldwide, with a strongly increasing prevalence that leaves two thirds of patients with long-term upper-limb impairments, impacting their independence and quality of life. Neurorehabilitation in stroke is a complex and challenging field, challenged by a limited understanding of the neural mechanisms underlying recovery as well as the lack of effective strategies to target these mechanisms and efficient biomarkers to evaluate and monitor therapy response.

We aim to address these challenges by combining non-invasive brain stimulation (NIBS) using transcranial magnetic stimulation (TMS) and a cortical, focal optical imaging approach using near-infrared imaging (NIRI). Our goal is to combine these two promising technologies and transfer them into a clinically viable solution to provide neurotherapy to stroke patients. The utilization of biomarker-guided assessments for novel interventions aligns with the contemporary paradigm shift towards personalized medicine in stroke research and clinical practice.

In the framework of a Bridge Discovery project, we are opening two PhD positions to advance the individualization of stroke treatment through the integration and active targeting of the underlying brain mechanisms by means of TMS and NIRI. One PhD position focuses on the technical implementation of the project, the other on the clinical application and validation of the approach. As the doctoral student focusing on the signal processing part in this project, you will be responsible to maximize robustness and signal content of the NIRI brain signals, integrate TMS and NIRI into a combined system, and implement a real-time neurofeedback pipeline. You will validate the algorithms on in-vivo NIRI data, generate and evaluate full-head brain images, investigate AI-supported classification of brain patterns and support the second PhD student in the clinical application of the system.

Job description

Your tasks will include:

• Familiarize with the NIRI system developed at RELab (optohive) and the TMS system available at Cereneo
• Define requirements for the data processing and visualization of NIRI data based on literature and clinicians’ input
• Explore signal processing algorithms for real-time and offline applications
• Implement a real-time neurofeedback pipeline, machine-learning classification, and AI-supported biomarker extraction related to stroke rehabilitation
• Develop an integrated setup combining TMS and NIRI for the co-registration of brain coordinates
• Establish and validate a framework to simulate and analyze NIRI brain recordings
• Plan and coordinate the conduction of studies to validate the implemented algorithms in healthy subjects and patients
• Disseminate research outcomes at international conferences and in peer-reviewed journals
• Actively contribute to grant writing

We are looking for a candidate that can start as soon as possible.

Your profile

You will have:

• A Master’s degree in Biomedical Engineering, Electrical Engineering, Information Systems, Computer Science, or related fields
• Experience with software engineering and, in particular, real-time signal processing. Prior experience in machine learning and AI are an advantage
• Extensive experience with Python
• Strong interest in neurorehabilitation and neuroscience. Prior knowledge in brain anatomy/mechanisms is a plus
• Curiosity and motivation to perform scientifically rigorous experimental work
• Excellent communication and interpersonal skills
• Willingness to work with patients and clinicians
• Self-motivation, ability to work independently and solution-oriented mentality
• Good oral and written English skills and fluency (B2) in German is a requirement
• Willingness to support teaching and supervise MSc/BSc student projects

We offer

• A unique and stimulating work environment within a strong and very motivated team
• An interdisciplinary team. Collaborations with clinicians and industries
• A project with a strong translational focus
• Competitive salary according to ETH standards for doctoral students

Working, teaching and research at ETH Zurich

We value diversity
In line with our values , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.
Curious? So are we.

We look forward to receiving your online application with the following documents:

• Cover letter outlining your motivation and experience in the field. Mention your earliest possible starting date
• CV including degree certificates
• Transcript of records

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about the Rehabilitation Engineering Laboratory (RELab) can be found on our website . Questions regarding the position should be directed to Dr. Dominik Wyser, [email protected]  (no applications).

For recruitment services the GTC of ETH Zurich apply.

About ETH Zürich
ETH Zurich is one of the world’s leading universities specialising in
science and technology. We are renowned for our excellent education,
cutting-edge fundamental research and direct transfer of new knowledge
into society. Over 30,000 people from more than 120 countries find our
university to be a place that promotes independent thinking and an
environment that inspires excellence. Located in the heart of Europe,
yet forging connections all over the world, we work together to
develop solutions for the global challenges of today and tomorrow.
Requirements

Research Field

Engineering

Years of Research Experience

1 - 4

Research Field

Engineering

Years of Research Experience

1 - 4

Research Field

Computer science

Years of Research Experience

1 - 4

Research Field

Engineering

Years of Research Experience

1 - 4

Research Field

Computer science

Years of Research Experience

1 - 4

Additional Information

Website for additional job details

https://academicpositions.com

Work Location(s)

Number of offers available

1

Company/Institute

ETH Zürich

Country

Switzerland

City

Zurich

Postal Code

8006

Street

Rämistrasse 101

Geofield

Where to apply

Website

https://academicpositions.com/ad/eth-zurich/2024/doctoral-position-in-digital-h…

Contact

City

Zurich

Website

https://ethz.ch/en.html

Postal Code

8006

STATUS: EXPIRED