Senior Applied AI Researcher, Digital Biology
Required skills
PhD in Machine Learning, Computer Science, Engineering, or a related discipline, 8+ years of hands-on experience in developing, training, and deploying deep learning models at scale, including LLMs, Transformers, SSMs, and/or generative models, Strong expertise in distributed training, optimization, and inference, Proven ability to lead independent research, implement robust solutions, and rigorously evaluate performance, Track record of publications and presentations at top conferences, Strong programming skills in Python and C++, with experience in PyTorch and/or CUDA, Excellent communication skills and ability to thrive in a dynamic, research-driven team.
Preferred skills
Experience with multimodal learning and integrating diverse data modalities, Experience with agentic AI frameworks or systems (e.g., tool-augmented models, planning-based agents, or multi-agent systems), Background in bioinformatics or digital biology, with experience working across interdisciplinary teams spanning research, engineering, and clinical domains, Experience in building or implementing digital twin systems, simulation frameworks, or data-driven modeling in healthcare or related domains.
Technologies
Large Language Models (LLMs), Transformers, State Space Models (SSMs), multimodal learning systems, agentic AI systems, digital twin systems, distributed training, PyTorch, CUDA.
Responsibilities
Conceptualize, design, and implement novel deep learning architectures for biological data, Develop multimodal learning systems that integrate heterogeneous data types, Develop foundational and generative models and agentic AI systems, Develop digital twin systems for healthcare, Implement deep learning systems integrated with agents, Evaluate model performance, analyze results, and iterate on designs, Apply knowledge of distributed training to build high-quality code, Collaborate closely with a diverse team of researchers, bioinformaticians, and domain experts.
Seniority
Senior
Domain
Digital Biology, Artificial Intelligence, Machine Learning, Computational Medicine, Health Platform
