Generative AI for Research & Innovation
Presented by Celoris Designs. To equip scientists and research engineers with the tactical skills to integrate advanced AI agents (GPT-4o, Claude 3.5, and upcoming GPT-5 class models) into the scientific method—from accelerating literature review to automating experiment protocols and predicting molecular properties.
To equip scientists and research engineers with the tactical skills to integrate advanced AI agents into the scientific method—from accelerating literature review to automating experiment protocols and predicting molecular properties.
Choose one track to build a portfolio-ready asset that demonstrates your mastery of AI in R&D.
Fine-tune a model on successful grant applications to draft methodology sections.
Build a tool that identifies failure points in lab protocols based on chemical properties.
A pipeline that screams a library of small molecules for binding affinity to a target protein.
Save hours of manual labor in reading, pipetting planning, and coding immediately.
Position yourself as one who commands AI rather than being replaced by it.
Pharma and Biotech companies are aggressively hiring 'AI Leads' for wet labs.
Shift from Hypotheses to Protocols in seconds using the latest model classes.
"This course completely changed how I approach research. I went from spending weeks on literature review to generating structured hypotheses in hours. The module on protocol optimization alone saved my lab months of trial-and-error."
PhD Researcher – Biotechnology
"I was skeptical about AI in wet labs—this course removed that skepticism fast. Automating protocol checks and predicting failure points using AI agents felt like having a senior postdoc working 24/7."
Senior Wet Lab Scientist – Pharma
"The chemistry and materials modules were incredibly practical. I built a virtual screening pipeline during the course that we are now actively evaluating for internal R&D."
Materials Science Engineer
"The way LLMs were framed as scientific reasoning engines—not just chatbots—was eye-opening. The self-driving lab concepts feel like the future, and now I actually know how to build them."
Postdoctoral Fellow – Computational Biology
"I didn’t have strong coding skills, but the workflows were explained clearly enough that I could still implement real AI tools. The data analysis module alone justified the course fee."
Research Scientist (Early Career)
"This course helped me bridge the gap between AI hype and real lab execution. We’re now using AI-assisted experiment design in our startup, and it’s already improving reproducibility and speed."
Founder – BioTech Startup
"The automated literature review and hypothesis generation module felt like cheating—in the best way. I used the techniques directly in my thesis proposal and my advisor was genuinely impressed."
MSc Student – Life Sciences
"Finally, a course that understands both science and modern AI. The sections on hallucinations, IP, and reproducibility were especially valuable—this isn’t just powerful, it’s responsible."
Research Engineer – AI & Science
"What surprised me most was the immediate ROI. We’re already saving hours every week on protocol planning and data cleanup. This course pays for itself very quickly."
Lab Manager – Molecular Biology
"This is not a theoretical AI course—it’s tactical and deeply relevant to real research. It helped me rethink my entire workflow, from idea generation to execution."
Senior Scientist – Academia
Validate your expertise in AI for scientific research, lab automation, and biotech innovation.
50 questions covering AI models, biotech startups, lab architecture, and research methodologies.
Pioneering AI in Science
Specifically focused on the intersection of LLMs, Robotics, and Bench Science. We bridge the gap between AI engineering and wet lab innovation.