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Data Science and Chemistry Applied In-Vivo



VitalTrace is a high growth medical device company founded and based in Perth, and currently developing a world-first biosensor aiming at detecting fetal distress during labour. VitalTrace were recently granted Breakthrough Device Designation by the FDA and have a growing team based in Perth and Melbourne.


VitalTrace was founded in 2017 after the founders met during a Stanford Spark Co-Lab and has been driven by raised Seed, Series A and grant funding. Vitaltrace is seeking to usher in a new age of childbirth monitoring, both minimalist in its application and much safer and reliable than current practice.


The team is a thriving, purpose driven MedTech company, striving to improve the way babies are born. Our mission is to develop cutting edge technology to empower all obstetricians and midwives to deliver the greatest outcomes for mothers and babies during labour.


The project spans two business units; Data Science and Chemistry which will work in parallel to explore the application of science in research & development.


For data science, key project outcomes will be the development of BI Dashboards, after conducting relevant in-vivo trials, exploratory data analysis of the in-vivo trial data, assessing ML models and Data Versioning using baseline algorithms for all in-vivo data in parquet format.


Chemistry will cover enzyme assay development, R&D into new formulations and subsequent analysis of the aforementioned activities.


Learn More

Mother Holding Baby Finger

Claire Li

The University of Western Australia

Biomedical Sciences


Skills: Technical skills in molecular biology, bone biology, cell biology, infectious diseases & biochemistry (qPCR, WB, cell culture, IF, etc), image & data analysis (ImageJ, GraphPad Prism), organisational skills, ability to priorities, attention to detail, communication & interpersonal skills, and teamwork.

Hassan Mahmood (002)_edited.jpg

Hassan Mahmood

Edith Cowan University

Science, Computing and Security


Skills: Machine/ Deep Learning, computer vision & embedded systems, programming with Python, Pytorch, Tensorflow etc, multidisciplinary and team work.

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