Tarrosion

SecureBio is a nonprofit working to protect the world from catastrophic pandemics. We operate the world’s largest metagenomic biosurveillance network, which performs daily sequencing of wastewater samples and nasal swabs to screen for emerging pathogens. Our computational team develops detection pipelines responsible for rapid processing of deep sequencing data in order to flag potential threats.

I'm the hiring manager for two roles:

- Senior infrastructure engineer, to own cloud infra, devops, CI/CD, AWS security, etc. https://securebio.org/careers/2026-cloud-infra-engineer/

- [Senior] software engineer focused on high performance data pipelines. https://securebio.org/careers/2026-software-engineer-pipelin...

Prior experience with biology or bioinformatics is not required. If you're interested, please apply via the relevant job posting. Feel free to drop me a line with questions; email is in my profile.

https://securebio.org/careers/

Cambridge, MA, USA (metro Boston) | ONSITE strongly preferred; REMOTE (US east coast) possible for exceptional candidates

SecureBio is a nonprofit working to protect the world from catastrophic pandemics. We operate the world’s largest metagenomic biosurveillance network, which performs daily sequencing of wastewater samples and nasal swabs to screen for emerging pathogens. Our computational team develops detection pipelines responsible for rapid processing of deep sequencing data in order to flag potential threats.

I'm the hiring manager for two roles:

- Senior infrastructure engineer, to own cloud infra, devops, CI/CD, AWS security, etc. https://securebio.org/careers/2026-cloud-infra-engineer/

- [Senior] software engineer focused on high performance data pipelines. https://securebio.org/careers/2026-software-engineer-pipelin...

Prior experience with biology or bioinformatics is not required. If you're interested, please apply via the relevant job posting. Feel free to drop me a line with questions; email is in my profile.

https://securebio.org/careers/

I often write with Claude, and at work we have Gemini code reviews on GitHub; definitely these two catch different things. I'd be excited to have them working together in parallel in a nice interface.

If our ops team gives this a thumbs-up security wise I'll be excited to try it out when back at work.

This I don't understand, maybe someone help me out? Say the real growth rate of capital (or interest rate available to me, whatever) is 2%/year and I have a 10 year time horizon. So $1.00 today is ~$1.22 in 10 years. More generally, if I have wealth X today I will have 1.22X in 10 years. And if X is not a constant but a random variable and I want to maximize future expected wealth (not log wealth), that's just max(E[1.22X]) and by linearity of expectation I should just maximize wealth today to maximize in 10 years time.

So Kelly being appropriate must have some other conditions, right? Wanting to maximize log wealth is surely sufficient (and individually probably ~rational). What else?

[1]

Tiny example (which blends Julia-the-language and Julia-the-ecosystem, for better and worse): I just timed reading the most recent CSV I generated in real life, a relatively small 14k rows x 19 columns. 10ms in Julia+CSV+DataFrames, 37ms in Python+Pandas...ie much faster in Julia but also not a pain point either way.

Remote: strongly prefer in person or hybrid

Willing to relocate: I'm very happy in the Boston area, so only under extraordinary circumstances

Technologies: data science, machine learning, technical communication, simulation, optimization, physically motivated models, heuristics; Julia, Python (Django, numpy, scipy, sklearn, cupy, pandas), AWS, Postgres/Postgis, Snowflake, Gurobi, NLopt, etc.

Resume: https://www.dropbox.com/scl/fi/wevhopcf81vx6vdoarn5a/efields...

Email: in the resume

Blurb: PhD in operations research -> startup employee #2 -> scale startup, gradually moving from data science IC to VP of data science + software engineering -> now looking for mission-meaningful hands-on technical work. I'm particularly good at technical communication as well as translating from the physical world (science/business) to math models. Open to companies of any size, especially motivated by the biosecurity, biotech, robotics, and clean energy sectors.

Something cool I built that's not work related: https://nomai-writing.com/ in the spirit of Outer Wilds

Remote: strongly prefer in person or hybrid

Willing to relocate: I'm very happy in the Boston area, so only under extraordinary circumstances

Technologies: data science, machine learning, technical communication, simulation, optimization, physically motivated models, heuristics; Julia, Python (Django, numpy, scipy, sklearn, cupy, pandas), AWS, Postgres/Postgis, Snowflake, Gurobi, NLopt, etc.

Resume: https://www.dropbox.com/scl/fi/wevhopcf81vx6vdoarn5a/efields...

Email: in the resume

Blurb: PhD in operations research -> startup employee #2 -> scale startup, gradually moving from data science IC to VP of data science + software engineering -> now looking for meaningful hands-on technical work at a company inventing something in the world of atoms

Something cool I built that's not work related: https://nomai-writing.com/ in the spirit of Outer Wilds

* Car users are quite dependent on the government for transportation, e.g. the many billions (in the US) of public dollars spent on roads each year. Hard to get around without them!

* Even if we hand-wave that away and assume car users aren't dependent on the government for transportation, surely _everyone_ is dependent for other reasons like enjoying public goods (national defense, clean air and water, rule of law), access to the social safety net, etc.?

I know spaced repetition is super helpful and I should be making and study cards to help with language learning and other topics I'm studying, but it always feels like a slog to try to find a deck (which won't end up being what you want) or manually make a bunch of cards, the UI is a little meh, etc.

I've long been frustrated that micromobility is held to a standard no other transportation mode is expected to meet, at least in the US. E.g.

- "Micromobility doesn't make any sense, you can tell because all the companies lose money." But every other form of transportation is deeply subsidized! In the US we spend hundreds of billions of dollars per year on roads, trains get federal infrastructure money, public transit [where it exists] isn't close to fully paid for by fare revenue, airlines get bailed out in recessions, all carbon-burning transport has an unpriced carbon externality, etc.

- "I hate the scooters, they clutter sidewalks." Often the clutter is real and a problem and I wish people behaved better. Among the people who I wish behaved better, I'd include car drivers who park in bike lanes or on sidewalks, yet the prevalence of such behavior doesn't create widespread calls to ban all cars. (Well, in some corners of the internet...)

More generally, it's weird that scooter companies are liable - legally or de facto - for such behavior at all. If I get a rental car from Hertz or similar and then park illegally, nobody claims this means Hertz should get a ticket or be shut down. Why are scooters different?

At the end of the day, in the US we've built our legal regime and land use patterns around the assumption that most travel should be by car and this travel should be subsidized. The fact that scooters create some frictions by taking up some of the space left over by cars is more an indictment of the system than of scooters.

1/4 drop in mortality just from fiber seems...like too much? Am I missing something subtle about how these mortality reduction effects are defined? Or perhaps these are conditional expectations but not causal effects? (Example: if eating fiber is negatively correlated with binge drinking alcohol, then P(death|fiber) probably << P(death|~fiber), but it's unclear a priori how much of that difference is due to alcohol)

Sporadically updated, but I'm pleased with most of the posts. It's a mix of personal reflections and some personal tech projects.

But people do that, in part, because cities don't provide good alternatives. A city the size of Paris probably has literally millions of on-street parking spots, or at least hundreds of thousands. (E.g. NYC has ~3 million [1]). Each car-sized parking spot can fit 12 scooters. So replacing 5% of parking spots with micromobility parking would provide space for something like 500,000 shared micromobility vehicles. For context, that's order of magnitude larger than the number of e-scooters in Paris.

(FWIW, Paris is maybe not a perfect example here; it's a relative leader in reclaiming space from cars for shared mobility and biking and such. Also when I was there last summer the scooters weren't a nuisance at all because they were overwhelmingly parked in marked areas, not littering sidewalks. YMMV.)

But especially in the US, we're so entrenched in thinking that only cars can be real mobility that we can't imagine shifting even 1% of the space and money we spend on cars towards more shared and less polluting forms of transportation. It sucks.

[1] https://gothamist.com/news/how-else-could-nyc-use-its-12-cen...