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Applied quantum computing in Life Sciences

Quantum and AI hybrid algorithms for near-term applications in the life sciences. Quantum (bio)sensing and communications for healthcare applications.

Mission

To apply quantum technologies to help improve the quality of people’s lives and of the environment.

Research

Together with partners, we are identifying, promoting and unlocking the potential of quantum technology in life science applications and are developing a platform to integrate quantum computing into industry. Use cases range from securing healthcare data in hospitals with quantum communications to using hybrid quantum-classical algorithms for intractable chemistry challenges and speeding-up drug discovery.

Our team explores methods to bring solutions in the short term with imperfect quantum computers (so called NISQ, for Noisy Intermediate Scale Quantum era), for instance with parallel quantum computing approaches, quantum simulations or hybrid quantum-classical algorithms. We study how to scale up quantum computing systems.
We have a strong effort to develop a solver for de novo molecular structure, dynamics and interactions elucidation, from various spectral data based on AI and quantum computing engines. It enables high-throughput advantage for time-sensitive analytics required in a variety of life science applications such as drug and material discovery. Usage ranges from efficient energy harvesting and storage to uncovering novel pharmaceutical drug candidates.

We also investigate more sensitive sensing devices using advanced quantum sensors to detect or visualize human physiology accurately at the body or molecular levels. Our work focuses on developing the next generation of (bio)medical quantum sensors for healthcare. Our aim is to speed up and improve patient care decisions, starting with diagnosing cardiovascular diseases.

Teaching

Applied quantum computing (life sciences) and science entrepreneurship (medical).

Open Science and venture building

We are committed to Open Science. We use arXiv and Zenodo as freely accessible repositories for sharing our research publications and data sets when applicable. Our measurements and data analysis codes are made available online to allow scientists to reproduce the results from our publications.

We launched HackLife to bring top global AI, quantum computing and healthcare experts from both industry and academia to explore solutions to challenges from drug discovery to pharmacovigilance, integration of clinical, lab, digital and multi-omics data, prediction of pandemics, radiology, healthcare access in developing regions etc.
Please contact us if you are interested.

Collaborations and projects

If you are interested in collaborating, for academic or industrial projects, please directly reach out to Y2xlbWVudC5qYXZlcnphY0BmaG53LmNo. We can run various types of projects such as Innosuisse projects, direct industrial research projects and consulting projects. We also support the creation and development of start-ups. Our knowledge transfer and IP policies are highly favorable for external collaborations.

If you are interested in proposing a subject for a student project or internship, please directly reach out to Y2xlbWVudC5qYXZlcnphY0BmaG53LmNoLg==


Institut für Medizintechnik und Medizininformatik

Fachhochschule Nordwestschweiz FHNW Hochschule für Life Sciences Institut für Medizintechnik und Medizininformatik Hofackerstrasse 30 4132 Muttenz
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