Lila Sciences
Life Sciences
Principal/Sr.PrincipalBioMLScientist
“Principal / Sr. Principal BioML Scientist at Lila Sciences. Skills: BioML, AI for Cell Biology, Autonomous-Science Platform, Target Identification. Grow and lead applied science footprint. Recruit, mentor, and develop scientists”
What You'll Achieve.
Deliver real computational biology; Set the technical bar for incoming scientists; Grow scientific judgment and execution standards; Own what makes a benchmark biologically meaningful; Own what evidence threshold turns model output into decision; Own what counts as platform delivering new science
Industry & Context.
What They're Looking For.
Must Have
PhD in Computational Biology, PhD in Computational Genomics, PhD in Machine Learning, Track record of impact in computational cell biology, Track record of impact in target identification, First-author publications at Nature, First-author publications at Science, First-author publications at Cell, First-author publications at Nature Methods, First-author publications at Nature Biotechnology, First-author publications at Nature Medicine, First-author publications at ICLR, First-author publications at ICML, First-author publications at NeurIPS, Experience translating computational research into deployed capability, Cross-functional collaboration
Nice to Have
Equivalent industry impact through deployed platforms, Equivalent industry impact through applied research, Track record of having pushed for or led a methodological shift, Experience scoping or supporting external partnerships, Experience with Lab-in-the-Loop, Experience with closed-loop workflows, Experience working alongside therapeutic-modality teams, Contributions to open-source tools, Contributions to open-source benchmarks, Contributions to open-source datasets, Experience in early-stage or 0→1 environments
What You'll Do.
Grow and lead applied science footprint
and develop scientists
Co-architect AI-for-Cell-Biology platform
closed-loop experimentation
Own applied and translational BioML charter
Translate research into deployable tools
Anchor applied program in target identification
Pioneer applied platform use
Run closed-loop experiments
Compose AI and lab-automation
Generate scientific results
Provide product-shaping feedback
Mentor research pod leads
Shape evaluation framework
Serve as scientific liaison
Represent team's research externally
How You'll Work.
Team & Collaboration
Partnering with AI/ML Science and Engineering leads; Collaboration across experimental scientists; Collaboration across computational biologists; Collaboration across platform engineering; Collaboration across product stakeholders; Collaboration across business stakeholders; Serve as scientific liaison to product; Serve as scientific liaison to partnership functions
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