Founding Scientist, Cell & Assay Biology

$120,000 - $180,000 per year.

$10k referral bonus for successful hires (half equity, half cash).

It’s Monday, 10 AM. You walk through the glass doors at the company's San Francisco headquarters, grab a coffee, grab a Red Bull, and pull up the overnight dashboard. Yesterday's mouse data has already been crunched. The house AI parsed the PK curves, flagged the outliers, and ranked the candidates while you slept. Two peptides from last week's batch showed decent half‑lives.

One was a dud. You skim the summary, make a note, and move on.

At noon, the head of science from a major AI lab walks in. He's got access to a frontier model that isn’t public yet and wants to understand your assay data well enough to train on it. You spend forty‑five minutes at the whiteboard explaining dose‑response curves to someone who understands transformers better than anyone alive but has never pipetted anything.

At 1 PM, the chemist hands off six candidates. Synthesized, purified, QC’d. You run them through the GPCR functional assay. Most do roughly what you'd expect — modest activity, nothing to write home about.

But one of them is oddly potent. Not a little. A lot.

In the next room, an automation engineer finishes programming the Open Trons to run your assays faster. She calls you over to validate the protocol under your supervision — by next week, this step takes half the time.

By 5 PM it's dosed in mice. By 8 PM you have preliminary data.

One day. Synthesis to animal data. One day.

The team goes to dinner at the poké spot in Mission Bay. Someone argues about whether the potency data is real or a lucky artifact. You think it's real, but you don't say that yet. You'll know tomorrow.

The Mission

In the age of ever‑improving AI capabilities, we humans are lagging behind. We're hungry, distractable, tired. A third of our day is spent unconscious. Half of us get cancer, half of us get heart disease. We're incapable of sustained high performance. We fall ill. The modern world feeds us slop that leads even further down the drain.

We believe that humans are capable of more.

We believe in excellence. We believe in superpowers. We believe in the extraordinary.

We're a small core team. In 6 months, we have designed 270+ therapeutic candidates, run 72+ placebo‑controlled mouse trials, and completed 79 custom syntheses. We're planning first‑in‑human safety for 2026 — which would be a world record for a non‑vaccine therapeutic built from scratch. Our founding scientific advisors include Professors at Harvard and MIT. At the pre‑seed stage, we raised $12M in funding from the best investors in deeptech.

What does a future look like where we can systematically identify, validate, and induce beneficial capabilities?

You'll be one of the founding scientists at the company. We're targeting first‑in‑human dosing by mid‑2026. If we hit it, this is also a world record for moving a non‑vaccine therapeutic into the clinic from scratch.

Most biotechs take weeks to go from synthesis to animal data. Here, it happens in one day. You synthesize peptides in the morning, run them through our cell assays by afternoon, test top candidates in mice by evening, and hand the results to our ML team overnight to design the next version. We do not know of another lab on earth running this loop at this speed.

Start‑ups are unique. Roles aren't as ossified or constrained as in a large corporation—you'll often learn a new role every few months, enabling you to grow as a person and team member. Keep this space for growth and variability in mind when reading this rough outline of what working together could look like.

As we are spinning out multiple deep research projects, if you want to lead your own program, we are open to that. Weird ideas are welcome!

More concretely, you will…

• Run the assays that decide which candidates move forward - mammalian cell culture (HEK
  293T, CHO‑K1), GPCR functional assays (calcium flux on the Flex Station 3, cAMP via HTRF), potency testing across dose-response panels on our top peptides

• Set up assays from scratch and make sense of early‑stage data - build stable cell lines, optimize plate‑based readouts, run peptide QC on HPLC, and turn…