Your role is to automate the processing of biochemical databases and to develop modelling software for hit-to-lead compound optimization.
- PhDs in quantum chemistry, molecular biology or a related discipline.
- Three or more years of experiences in medicinal chemistry and hit-to-lead optimization for neurodegenerative diseases at a pharmaceutical company.
- Three or more years of experience in structure/ligand-based drug design, pharmacophore modeling, pharmacokinetic and pharmacodynamic data analysis and modeling, molecular docking, virtual screening, QSAR,or other computer-aided drug design techniques.
- Capable of working independently and overcoming challenges without supervision while being a team player.
Desired skills and experience
- Three of more years of experience in product-level application of deep neural networks in drug discovery or medical diagnostics.
- One or more publications in Nature, Science, Nature Neuroscience, Nature Methods, Nature Protocols, NIPS or other high-impact journals or conferences.
- Professional knowledge and practice of Python, Bash, Perl, or other scripting languages.
- Experience with cloud computing environments (AWS, Azure, etc.).
- Comfortable with both a logic analyzer and a wrench.
- Exceptional ability and track record of developing original and unconventional ideas/theories/models/inventions based on rethinking/reinventing the first principles of single or multiple fields.
Desired personal qualities
- First-principles-based thinking
- Extraordinary composure and integrity in face of dire condition
- Ruthless rationality and candor in the pursuit of knowledge
- Profound empathy and charitableness in the matter of people
- Resilience and fearlessness working outside your comfort zone
- Described by others as the most radical yet humblest researcher / engineer / thinker they know
- Intellectual breadth
- Sense of humor
Application without a cover letter will not be considered.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.