
inbiome is a pioneer in molecular diagnostics, offering a patented Molecular Culture technology that significantly accelerates bacterial diagnostics and microbiome analysis. Their proprietary…

inbiome is a pioneer in molecular diagnostics, offering a patented Molecular Culture technology that significantly accelerates bacterial diagnostics and microbiome analysis. Their proprietary…
SCIENTIFIC ENGINEER
Build the algorithms that turn noisy machine signals into life-changing diagnoses.
Welcome to inbiome
At inbiome, we are building the next generation of molecular diagnostics. Bacteria shape human health in profound ways, yet clinicians still face high-stakes decisions armed with slow, imprecise tools. We are changing that.
Our Molecular Culture ID platform reduces diagnostic time from days to hours through a combination of molecular biology, signal processing, physical modelling, and inference — producing clinically actionable results at the point of care.
We work closely with more than 20 leading hospitals across Europe and the United States to ensure our assays are clinically relevant, rigorously validated, and embedded in real-world care pathways.
inbiome is a fast-growing scale-up located at the Amsterdam Science Park. Our international team of around 30 colleagues combines molecular biology, data science, hardware engineering, and software development, working as a tightly integrated unit with a shared mission.
We are now looking for a Scientific Engineer to join our core R&D team and help build the algorithmic backbone of our diagnostics platform.
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The Role: Scientific Engineer
Inbiome is at the forefront of molecular diagnostics, building systems that reduce diagnostic time from days to hours. We develop algorithms that recover real biological information from noisy, distorted machine signals, combining signal processing, physical modeling, inference, and scientific software.
The work is about understanding machines, chemistry, and biology deeply enough to recover robust underlying structure from imperfect measurements.
You will help design, build, and improve algorithms that interpret structured measurement data from a real-world diagnostic workflow.
Your work will include:
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Understanding how instrument behaviour, chemistry, and operating conditions distort measured signals
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Identifying stable underlying structure beneath noisy, real-world observations
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Designing robust inference methods that remain interpretable and well-bounded
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Improving quantitative estimation and uncertainty handling across the diagnostic pipeline
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Translating scientific insight into practical software used in production
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Collaborating closely with molecular biology, hardware, and clinical teams to ground your models in experimental reality
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Who We Are Looking For
You may come from electrical engineering, applied physics, control engineering, scientific computing, or another strongly quantitative field. Your exact background matters less than how you think.
You may be a strong fit if you enjoy:
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Reasoning from first principles
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Working with noisy real-world data
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Uncovering structure in complex data
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Turning ideas into working tools and software
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Working in close collaboration within a multi-disciplinary team
We also value people who are comfortable using AI tools like LLMs and agents as a natural part of technical problem-solving and day-to-day work.
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What We Offer
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A technically rich environment where your work directly shapes a product that reaches clinicians and patients
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Deep, first-principles problems at the intersection of measurement science, biology, and software
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You'll work in a small, highly capable team where your contributions are visible and your voice is heard
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Competitive salary including 13th month, pension scheme, and employee stock options
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Hybrid working flexibility and travel allowance
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Apply
We review applications on a rolling basis. To apply, please send your CV and a short note explaining why this challenge interests you to:
careers@inbiome.com
If your background is unconventional but the problem resonates, we still want to hear from you.
Accelerating diagnostics where it matters most
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