🛠 Tech Stack

💼 About This Role

You'll invent and exploit probabilistic generative models using diffusion models, normalizing flows, and flow matching for drug discovery at Achira. You'll drive measurable gains in molecular design and biomolecular conformational sampling.

🎯 What You'll Do

• Develop conditional small-molecule generators using diffusion models, normalizing flows, and flow matching.
• Design sequential sampling pipelines (SMC/AIS/tempering/Boltzmann generators) for ML potentials.
• Design learned proposal mechanisms (transport maps, score-guided moves) for multimodal landscapes.
• Use nonequilibrium statistical mechanics (Crooks/Jarzynski) to accelerate exploration.

📋 Requirements

• PhD in computer science, statistics, applied math, or related field.
• Track record in probabilistic ML and generative modeling.
• Industry experience with practical machine learning problems.
• Hands-on experience with diffusion/flows/flow matching on geometric data.

✨ Nice to Have

• Background in SE(3)-equivariant architectures or geometric deep learning.
• Experience with active learning/Bayesian optimization.
• Contributions to open-source scientific software.

🎁 Benefits & Perks

• 💰 Competitive compensation ($164,638 – $259,000 + equity + bonus)