Research Associate III - Protein Binding Screening & Prediction

Are you ready for new challenges and new opportunities? Join our team in Seattle! Current job opportunities are posted here as they become available.

The mission of the Allen Institute is to unlock the complexities of bioscience and advance our knowledge to improve human health. Using an open science, multi-scale, team-oriented approach, the Allen Institute focuses on accelerating foundational research, developing standards and models, and cultivating new ideas to make a broad, transformational impact on science.

Join our Artificial Intelligence-Powered Biological Design (AIPBD) lab, an initiative at the intersection of academic creativity and start‑up style execution. Our mission is to apply machine learning to biological design. Join us as we build a series of interconnected design‑test‑loop “flywheels” that enable design of synthetic enhancers, protein binders, and more.

AIPBD is looking for a research associate to join our protein binder flywheel team. The binder flywheel team is part of a larger effort that includes a total of three experimental flywheel teams and one machine learning team, and that will report into the Sea Hub administrative unit. The goal of the binder flywheel is to produce a model that can accurately predict the effect of amino acid substitutions on the binding of proteins to other proteins, small molecules, and nucleic acids.

To assist this flywheel team, you will need a strong background in high‑throughput library screening, flow cytometry, and NGS. You will work in the lab to optimize active learning processes in your flywheel. You will help to optimize your flywheel’s turnaround‑time and per‑cycle model improvement, racing to help deliver the best possible ML models for predicting the impact of mutations on protein binding.

At the Allen Institute, we believe that science is for everyone – and should be open to everyone. We are dedicated to combating biases and reducing barriers to STEM careers more broadly. We also believe that science is better when it includes different perspectives and voices. We strive to make the Allen Institute a place where everyone feels like they belong and are empowered to do their best work in a supportive environment.

• Execute and optimize protein library screening and binder evaluation experiments to generate high‑quality, model‑ready datasets
• Execute workflows including library construction, yeast display, flow cytometry analysis and sorting, NGS library generation, and sequencing
• Optimize high‑throughput screening workflows to improve assay robustness, turnaround time, and model‑learning efficiency
• Lead troubleshooting efforts to optimize generation of high‑quality datasets, from library construction through NGS sequencing
• Independently execute molecular biology protocols, including molecular cloning, PCR, flow cytometry and yeast culture techniques
• Review and analyze data, participating in quality control and troubleshooting of processes and results
• Collaborate closely with computational and machine learning scientists to improve experimental workflows and model performance
• Contribute to the development of new protocols as needed
• Present results and summarize progress in a multidisciplinary team to help frame internal decision‑making
• Comply with SOPs, good laboratory practices, and regulatory requirements
• Adhere to a team schedule and individual time management
• Other duties as assigned

Note:

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This description reflects management’s assignment of essential functions; it does not proscribe or restrict the tasks that may be assigned.

• Bachelor’s degree in Cell Biology, Genetics, Synthetic Biology, Bioengineering, Genomics, Molecular Biology, Bioinformatics, or related field
• Minimum 4 years of relevant experience

• Master’s degree in Cell Biology, Genetics, Synthetic Biology, Bioengineering, Genomics, Molecular Biology, Bioinformatics, or related field
• 6+ years of relevant experience
• Experience in teams where wet lab experiments primarily serve to build AI…