Biology Jobs 2026 (Now Hiring) – Smart Auto Apply

Conquest is building an AI-driven therapeutic development engine for cancer, anchored in high-content phenomics. We're not a traditional HTS shop — we care deeply about the richness of the biological signal, not just throughput. If you've spent time thinking about what Cell Painting or morphological profiling can tell you that a viability assay can't, you'll feel at home here.

We're a small, technical team, and we move fast.

What you'll actually be doing

You'll own the experimental side of our phenotypic screening platform. That means taking assays that don't exist yet and building them — not plugging into an established pipeline. You'll design experiments in oncology cell models, push them toward high-throughput, and work directly with our computational and AI team to make sure the data we generate is worth learning from.

A big part of this role is workflow automation in the truest sense: figuring out what a skilled human currently does at the bench, understanding why it works, and then re-engineering it so a robot does it reliably at scale. If your prior experience with automation was mostly operating someone else's system, this probably isn't the right fit. If you've ever looked at a manual step and thought "I could write a protocol that makes this disappear," keep reading.

You'll also have room to explore. We're genuinely interested in novel assay formats — live-cell, morphological profiling, functional readouts — and we want someone who brings ideas, not just execution.

What we're looking for

• PhD and/or postdoc in cell biology, bioengineering, or a closely related field — with real bench depth, not just oversight experience

• Experience in phenotypic profiling — Cell Painting, morphological profiling, or related approaches — is central to this role, not a nice-to-have. We want someone who has opinions about what makes a good phenotypic readout and why

• Demonstrated ability to build or meaningfully improve a workflow, not just run one — startup experience where you were hands-on from day one is exactly what we're after

• Comfort working in oncology models (2D, 3D, co-culture — ideally all of the above)

• Collaborative instincts: you'll be working closely with computational biologists and AI engineers, and the quality of the biology determines the quality of the model

• Intellectual curiosity about the why behind experimental design, not just the how

This is a full-time, in-person role (5 days/week) in our Palo Alto lab.

Why Conquest

We're early. That means you'll have real ownership over what we build and how we build it — and you'll see the direct connection between your work at the bench and where the science goes. The leadership team has deep experience across AI, drug discovery, and oncology, and we're genuinely committed to doing this differently.

If you've been looking for the place where the biology is taken as seriously as the machine learning, this is it.