Data Generation for ML-based molecule design

At Inceptive, you will help pioneer the next generation of AI-designed drugs, with the potential to positively impact billions of people, as part of a collaborative, antedisciplinary team. We advance the state of the art in molecular design by training large-scale foundation models that enable cutting-edge generative approaches. You will collaborate closely with biologists and machine learning researchers to design, analyze, and improve the experiments that power our models.

• Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise; Develop statistical and computational approaches to characterize assay quality, reproducibility, and sources of experimental variation; Identify and investigate sources of bias and measurement artifacts in biological datasets; Design and analyze large-scale biological experiments that generate training and evaluation data for machine learning models; Partner with experimental scientists to improve assay design, controls, and data collection strategies; Collaborate with machine learning researchers to understand how experimental design decisions impact model training and evaluation; Analyze, visualize, and communicate findings to support decision-making across scientific and engineering teams

• PhD in computational biology, systems biology, genomics, bioengineering, biostatistics, biophysics, or a related quantitative discipline, or equivalent practical experience; Demonstrated track record of analyzing complex biological datasets and translating computational insights into experimental validation or new data collection; Strong foundation in experimental design, statistical analysis, and quantitative reasoning; Deep understanding of sources of experimental variability, batch effects, and assay artifacts in biological data; Capable programmer in Python and common scientific computing libraries; Excellent written and verbal communication skills, including the ability to communicate effectively across computational and experimental disciplines; Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET; Readiness to travel several times a year for company retreats and business events; We value the benefits of in-person collaboration and expect candidates to primarily work from our office locations