Build ML that detects disease before symptoms appear.

A fast-growing Berlin clinical AI startup is working at the intersection of machine learning, voice analytics, and cardiovascular care. Its systems are already used in real clinical workflows, and its next-generation research explores how human voice can act as a physiological biomarker for early disease deterioration.

This role offers a rare chance to work on a high-impact, high-difficulty ML problem where research is validated in clinical studies and translated into regulated, real-world systems.

Why this role stands out

• A genuinely novel ML challenge: extracting clinically meaningful signal from human voice.
• Clinical-grade impact: models are evaluated in real studies and deployed into care.
• End-to-end ownership: from hypothesis and experimentation to validation and productisation.
• Strong scientific environment: close collaboration with clinicians and experienced researchers.
• Work that matters: research can directly change how chronic disease is monitored.

What the role involves

• Designing and running ML experiments on voice and biosignal data.
• Developing and validating models for early detection of cardiovascular deterioration.
• Translating research outcomes into deployable, clinical-grade ML prototypes.
• Helping define research standards and mentoring junior researchers.

What they are looking for

• PhD or equivalent research experience in ML, signal processing, or related fields.
• Strong hands-on experience with Python and modern ML frameworks.
• A researcher driven by rigor, curiosity, and real-world impact.

For ML researchers who want their work to influence clinical practice — not just benchmarks — this is a rare opportunity.