Job Description

Summary:

We are looking for a PhD experienced @ the intersection of Bioinformatics and Machine Learning. Join us and work with our brilliant AI research team, + scientifically rigorous in-house experimentalists, to tackle various challenges. We are a highly collaborative team and excited to connect with computational scientists with systems thinking, a strong understanding of statistics, who are skilled in making bioinformatics discoveries, running directed analysis, and creating/developing cutting-edge AI for research.

Opportunity to:

• Design and implement large-scale bioinformatics analysis pipelines to process internal data and analyze published datasets.
• Facilitate training and integration of bioinformatics workflows with multi-agent LLM systems, including enabling model fine-tuning and creation of custom embeddings.
• Help develop and support our wet-lab and ML experimentation platforms for internal tools and projects.
• Guide the development of agentic or model-driven analysis tools.
• Provide advice and guidance on experimental design and project requirements in our wet lab.
• Collaborate closely with a multidisciplinary team of AI researchers, biologists, and chemists, while fostering an environment of innovation and discovery.

Must have:

• PhD. in Bioinformatics, Computational Biology, or related discipline.
• Experience working with a variety of biology data types, including NGS, scRNA-seq, proteomics, and others.
• Extensive working knowledge of and experience with standard bioinformatics tools for analyzing various data types.
• Strong programming expertise with the capability to adapt to various technical challenges in the experiment, data, and analysis stack.
• Demonstrated ability to build and maintain robust, production-level analysis pipelines.
• Strong practical understanding of statistics.
• Ability to stay current on the latest cutting-edge techniques in bioinformatics and AI.
• Desire to learn and build tools for AI-augmented bioinformatics analysis and science.

VERY nice to have:

• Familiarity with custom agents and other advanced ML/AI techniques such as RAG.
• Experience with machine learning tools and capabilities, especially experience training custom models, reinforcement learning, or other post-training techniques.

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