Data

At the Lab, our Data Team delves into the analyses of a variety of datasets spanning from genomics and multiomics to biomedical images, EMR and wearables data to uncover biologically meaningful or clinically actionable insights and tackle real-world challenges.

 

The team is made of two types of people: CS and data science specialists who are passionate about making an impact in biology or medicine and biotechnology or related graduates who have a strong numerical and/or coding skills and have a knack for data analysis. All of them working at the interface of AI, biology and medicine.

#genomics #digitalhealth #scienceed #networkbiology #Data #Epigenetics #ai4doctors

What We Look For

  • Proficiency in data analysis with Python and/or R, with bonus points for knowledge of sequence data, biomedical images or any other dataset in biology or medicine.
  • Experience with machine learning and deep learning experiments is preferable.
  • Resourcefulness, hacker/go-getter approach to problem-solving. A strong eye for detail and a good communicator who thrives in both team and independent settings.
  • Curious, dependable and passionate about making a meaningful impact in science.

What You’ll Do

  • Analyze genomic and multiomic data, digital histopathology images, and other biomedical datasets to uncover useful insights.
  • Have atleast one independent research project from concept to completion, supervised by the PI. Be in one or more team projects and/or ‘lateral collabs’.
  • Share progress and collaborate in weekly meetings, leveraging diverse expertise to enhance outcomes.
  • Engage in journal clubs, workshops, and research sprints to expand knowledge and foster innovation.

For Interested Thesis Students and Interns

  • Interested in Genomics and Multimoics? Learn more about opportunities to intern or undertake your FYP at the Lab and apply at bit.ly/bioinfo2025.
  • Interested in our new GenBio group? Learn more about how to intern or undertake your FYP at the Lab on the frontiers of GenAI and Biology and apply at bit.ly/GenBio2025.