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Engineering for clinical and research teams

Healthcare data is large, sensitive, and rarely where you need it. The work tends to be a mix of getting compute to researchers without them managing machines, making clinical content searchable, and running models against signals that were previously read by eye, all under uptime and privacy constraints that leave little room for experiments in production.

What we usually find in this sector

  • Research compute runs on individual workstations, so a job is limited by whose laptop it is on
  • Clinical documents exist but nobody can find the one they need without knowing where it was filed
  • Signal review is done by eye, and the volume is growing faster than the team
  • Anything touching patient data has to be defensible before it can be useful

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