Lab-first learning
Design experiments, calibrate instruments, and publish protocols you can reuse and share.
Science • 2026
Science that shapes tomorrow
At pilar168, we turn curiosity into measurable impact. Learn with researchers, build in the lab and in code, and test ideas against real-world data—from climate and biology to materials and AI.
Our approach is rigorously hands-on: open datasets, reproducible methods, transparent results. Let’s do the work that moves knowledge forward.
Explore CoursesFrom idea to prototype
Translate hypotheses into working prototypes using open hardware and modern toolchains.
AI-powered analysis
Leverage ML for image, signal, and genomic data while keeping methods transparent and fair.
Reproducible methods
Versioned code, preregistration, and peer review baked into every project.
Impact at scale
Work on climate resilience, public health, and sustainable materials with real partners.
Fast feedback
Weekly critiques with researchers and industry mentors to keep momentum high.
Built by researchers, for curious minds
pilar168 is a science studio and learning platform where rigor meets creativity. We believe that modern science thrives when methods are open, tools are accessible, and learning is active. Our curriculum blends fundamental theory with field-tested practice—think microscopy and wet labs alongside data pipelines, simulation, and hardware.
You’ll work in small cohorts, publish reproducible notebooks, and collaborate on projects that matter. By the end, you’ll have a portfolio that demonstrates how you reason, build, and validate—exactly what labs and teams look for today.
Courses with real-world datasets
Experimental Physics: Signals & Sensors
Build and calibrate low-noise measurement chains. Analyze signals from real detectors and publish a reproducible toolkit.
Bioinformatics with Open Genomes
Process sequencing data end-to-end—QC, alignment, variant calling—and communicate results with transparent notebooks.
Climate Data & Earth Systems
Interrogate satellite and sensor datasets to model trends, extremes, and resilience strategies under uncertainty.
What learners and partners say
Authentic feedback from recent cohorts and collaborating labs.
Maya P.
Graduate Researcher, Materials
The lab-first approach made the difference—I shipped a working spectroscopy rig and a clear analysis pipeline.
Louis K.
Data Scientist
Best blend of theory and practice. The emphasis on reproducibility changed how I present results at work.
Dr. Noor A.
Partner Lab PI
Students arrived prepared to discuss methods, not just conclusions. Excellent documentation and rigor.
Ethan R.
Cohort Alum
The mentors were present and honest. Weekly critiques pushed my project from good to publishable.
Join the next cohort
Tell us a bit about you and what you want to explore. We’ll follow up with schedule options and scholarship information.