Careers

We Make.
We Prove.

ProvaLabs builds tools that help life-science researchers measure and validate biological function. We turn ideas into prototypes, test them in real experiments, learn from what does not work, and improve quickly.

Make→Experiment→Measure→Prove→Improve

Open Positions

Our products bring together electronics, software, electrophysiology, and biological experiments. We are looking for people who can own their craft and work across those boundaries.

What you will do

  • Design and debug analog/digital circuits and PCBs.
  • Integrate ADC/DAQ, MCU, sensors, and instrument electronics.
  • Bring up prototypes, measure performance, and troubleshoot failures.
  • Support firmware, vendor builds, and production transfer as needed.

What we look for

  • Strong fundamentals in electrical/electronic engineering.
  • Hands-on PCB and hardware debugging experience.
  • Comfort using oscilloscopes and standard bench instruments.
  • Ability to think beyond a circuit and understand the whole instrument.

Nice to have

  • Low-noise analog design, embedded firmware, DAQ, test automation, or scientific instrumentation.
Biology or electrophysiology experience is not required.

What you will do

  • Develop acquisition, signal-processing, and analysis software.
  • Implement waveform features, algorithms, and visualization.
  • Work with scientists to validate analysis methods on real data.
  • Work with hardware engineers on device communication and acquisition.

What we look for

  • Strong software development experience in Python, C/C++, C#, or similar.
  • Comfort with numerical data, signals, and algorithm validation.
  • Ability to define solutions with researchers before requirements are fully specified.

Nice to have

  • DSP, electrophysiology/ECG/EEG/MEA, scientific computing, statistics, or waveform classification.
Understanding the measurement matters more to us than using AI for its own sake.

What you will do

  • Design and run electrophysiology experiments.
  • Interpret waveforms and define meaningful quantitative metrics.
  • Develop reference analyses and validate algorithms scientifically.
  • Shape new applications with software and bio R&D colleagues.

What we look for

  • Hands-on electrophysiology experience and strong biological interpretation skills.
  • Ability to turn experimental observations into measurable criteria.
  • Comfort collaborating closely with engineers.

Nice to have

  • Cardiomyocyte or neuronal EP, MEA/patch clamp, iPSC models, organoids/MPS, pharmacology, Python/MATLAB/R.
Production software engineering is not required, but quantitative analysis skills are important.

What you will do

  • Culture cells, prepare samples, and run biological assays.
  • Operate prototypes repeatedly and compare hardware/software revisions.
  • Document conditions, anomalies, and reproducibility.
  • Reproduce failures and test fixes with engineers and scientists.

What we look for

  • Hands-on mammalian cell culture and good experimental discipline.
  • Strong documentation and reproducibility habits.
  • Curiosity about unexpected results rather than simply working around them.
  • Comfort working with imperfect, evolving equipment.

Nice to have

  • iPSC, cardiomyocyte, neuron, organoid/MPS, microscopy, basic data analysis, or electrophysiology.
Electrophysiology experience is helpful, but not required.

How We Work

Prototype early. Test with real biology. Improve from evidence.

A prototype is not the last step before a finished product. It is how we discover what we missed. Noise, strange waveforms, inconsistent experiments, and unexpected software behavior are all useful when they help us identify the next problem to solve.

Imagine01
Prototype02
Experiment03
Measure04
Improve05
Repeat↻

Imaginative

Think beyond the current method.

Experimental

Test ideas instead of debating them endlessly.

Proficient

Move fast without compromising technical rigor.

Inventive

Turn ideas into tools that create real value.

Recruitment Process

1 · Apply
2 · Review
3 · Interview
4 · Join

We care less about perfect answers than about how you have built, tested, analyzed, and solved real problems. Bring work that helps us understand what you actually did.