Ap­plied quan­tum com­put­ing in life sci­ences, FHNW School of Life Sciences

Our team explores methods for short term use of imperfect quantum computers, which currently operate in the Noisy Intermediate Scale Quantum era. These methods include parallel quantum computing approaches, quantum simulations or hybrid quantum-classical algorithms. We study how to scale up quantum computing systems.

Securing healthcare data in hospitals.

We are developing a solver based on AI and quantum computing engines for de novo molecular structure, dynamics and interactions elucidation from various spectral data. 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.

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, and healthcare access in developing regions. Please contact us if you are interested in participating.