Adam Carnaffan / Engineer + founder
I design automated molecular systems from sample preparation and reagents through robotics, instrument control, sequencing, and analysis.
01 The job
The whole system is the product.
I work across the seams: biology and machines, research and operations, physical constraints and software abstractions.
A protocol is only as strong as the instrument running it. An instrument is only as useful as its controls. Analysis only matters when the entire loop returns a clear, trustworthy result.
I stay with that loop—finding the brittle interfaces and turning a promising demonstration into something people can actually operate.
Layers I have personally built or integrated
02 Selected work
Responsibilities, not just domains.
The useful part of working across disciplines is ownership: being able to follow a system from a biological sample to a physical mechanism to a software decision—and fix whichever layer is failing.
01
Kraken Sense / automated qPCR
I joined on the software side and grew into system integration across electronics, robotics, laboratory workflows, controls, and product testing.
The job was to make the layers agree: translate a wet-lab protocol into machine states, coordinate the physical process, expose failures clearly, and return a result an operator could trust.
Kraken Sense automated molecular testing02
Laboratory automation / sequencing
I developed sample-preparation and sequencing-library methods, then automated them through robotics to the point of sequencing. That work crossed assay design, liquid handling, instrument control, failure recovery, and validation.
I also worked on reagent formulations and room-temperature stability for enzymes, RNA-based materials, and oligonucleotides—because automation is only useful when the biology survives the real operating environment.
Kraken Sense sequencing preparation03
Magnus Biosciences / current
At Magnus, I am building systems that choose what to test, run experiments on automated laboratory infrastructure, analyze the result, and decide what should happen next.
The work connects experimental design, robotics, data capture, bioinformatics, and operations so that a discovery campaign is traceable and repeatable rather than a pile of disconnected research artifacts.
Magnus Biosciences04
Bioinformatics R&D / edge systems
I am exploring signal-processing and frequency-domain approaches to biological data that can move sequencing analysis away from GPU-heavy infrastructure and onto lower-power hardware.
The intended environment is the edge: places where a useful answer cannot depend on a data center, reliable connectivity, or abundant power.
03 How I work
The interfaces are where systems fail.
Trace the sample, protocol, hardware state, control logic, data, and operator action as one system.
Test the contamination, drift, dropped step, bad sensor reading, and recovery path before the field does.
A system is not finished when an engineer can run it. It is finished when the intended operator can trust it.
Logs, measurements, experimental outcomes, and costs should feed directly into the next decision.
04 Background
Engineering, academics, and a surprising amount of ice.
I studied Engineering Science at the University of Toronto, specializing in Machine Intelligence. Before engineering, I spent years in competitive ice dance—another activity where the details, interfaces, and failure modes are difficult to fake.