Computational design of biological experiments for model development

Role: Scientific Researcher focused on biological foundation models for AI-designed drug discovery, emphasizing understanding model behavior, data influences, and biological signals. Responsibilities: investigate model performance with varying data factors, develop meaningful biological evaluations, identify data artifacts and promising datasets, design experiments both computationally and in labs, collaborate with biologists and AI researchers to inform model and data strategies, analyze and communicate findings to guide research directions. Qualifications: PhD in computational biology, statistics, physics, machine learning, or related quantitative field; strong statistical and quantitative skills; experience analyzing high-throughput sequencing data (RNA-seq, genomics); proficient in Python; excellent communicator; willing to collaborate across US and Europe, with travel. Preferred: 3+ years post-PhD in computational biology or related research. High-Value: focus on biologically meaningful evaluation, model understanding, large-scale biological datasets, generative AI, and interdisciplinary collaboration in drug discovery. Work Setup: primarily on-site with travel; flexible to work across US and Europe hours.