Who we are π©βπ» π¨βπ»
Drug development is an expensive and complex process, with the average cost exceeding $1 billion per new drug. One of the major challenges is the unpredictability of chemical synthesis - determining how to create potential drug candidates requires significant expertise and resources.
At Molecule.one, we are leveraging AI to solve this challenge. By combining state-of-the-art machine learning with comprehensive chemistry data, we're developing an AI Chemist system that can automate complex chemical synthesis tasks.
Our key achievements include:
- Developing the first commercial AI-powered chemical synthesis planning software
- Being the first CEE startup to present at TechCrunch Disrupt SF (2019)
- Securing $4.6M in funding from leading US & European investors (2021)
- Strategic partnership with CAS to create an advanced Synthetic Accessibility Scoring platform (2023)
Our capabilities expanded significantly with the launch of our High-Throughput Experimentation (HTE) laboratory in 2022, which has already generated over 200,000 experimental data points. We're now growing further by:
- Creating compound libraries using our proprietary Spacem1 virtual library
- Opening a second synthetic laboratory in ΕΓ³dΕΊ
Our diverse team brings together experts in organic chemistry, software development, and machine learning, with over 25 talented professionals working together to revolutionize drug discovery. See the bottom of this page for more details on our core values.
Job description
Type: Full-time
We are looking for an experienced Organic Chemist passionate about applying computational methods to real-world synthetic challenges. This position combines hands-on laboratory expertise with data analysis skills, focusing on extracting valuable insights from experimental chemistry data to enhance our AI-driven synthesis planning capabilities.
Key Responsibilities
- Design and optimize synthetic routes focusing on coupling reactions (e.g., Suzuki, Buchwald-Hartwig, C-H activation).
- Plan and execute challenging transformations, with emphasis on heterocyclic chemistry and late-stage functionalization.
- Implement and integrate machine learning models predictions into synthetic processes.
- Document and analyze reaction outcomes, providing detailed procedures and characterization data.
Required Qualifications
- Minimum 3 years of experience in organic synthesis, with proven track record in planning and executing synthetic routes.
- Experience in medicinal chemistry and heterocyclic synthesis would be an advantage.
- Demonstrated ability to work independently and manage complex synthetic projects.
- Strong organizational and planning skills, with attention to detail in maintaining laboratory records.
- Proficiency in modern analytical techniques (NMR, HPLC, LC-MS) and structure characterization.