Scientist I - Protein Binding Screening & Prediction

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 Lab (AIPL), 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.

AIPL is looking for a scientist 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 SeaHub 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 protein library screening, protein binder design, or prediction of protein interactions with other molecules. You will work in the lab and collaborate with others, including machine learning colleagues, to optimize active learning processes in your flywheel. You will optimize your flywheel’s turn-around-time and per-cycle model improvement, racing to 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.

We are an equal-opportunity employer and strongly encourage people from all backgrounds to apply for our open positions.

Essential Functions

• Assist in the building and running of a rapid, repeatable design–test–learn pipeline focused on protein binding
• Perform protein library screening and binder evaluation experiments to generate high-quality, model-ready datasets
• Partner with machine learning colleagues to help define prediction targets, curate/structure data, and implement active-learning strategies that choose the next best experiments
• Assist in the optimization of flywheel performance by improving turnaround time, throughput, cost, and per-cycle model lift; identify and remove experimental bottlenecks
• Maintain accurate laboratory documentation using established methods
• Present scientific results and complex concepts internally in talks and progress reports
• Present results to the external community at conferences and in publications

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.

Required Education and Experience

• PhD in biochemistry, molecular biology, or a related field; or equivalent combination of degree and experience

Preferred Education and Experience

• 1 – 2 years relevant post-doctoral or post-grad biotech experience
• Experience designing or optimizing protein binders and characterizing binding (e.g., affinity/specificity) to proteins, small molecules, or nucleic acids
• Experience with protein library screening workflows (e.g., yeast/phage display + FACS/NGS or other high-throughput binder discovery platforms)
• Experience building or operating data-driven/active-learning experimental loops and translating assay outputs into model-ready datasets
• Experience with protein engineering/interaction prediction approaches and modern analysis pipelines (e.g., sequence-to-function modeling, structural modeling, or high-throughput data QC/processing)
• Experience with functional genomics, massively parallel reporter assays, multiplexed assays of variant effect, saturation mutagenesis, or plasmid library-based screening
• Experience performing molecular biology methods including library cloning, Golden Gate assembly, Gibson assembly, CRISPR/Cas9-editing, mammalian cell culture, stem cell culture, and NGS library prep

Work Environment

• May enter laboratory environment, including potential exposure to lasers, biohazards

Physical Demands

• Fine motor movements in fingers/hands to operate computers and other office equipment; repetitive motion with lab equipment

Position Type/Expected Hours of Work

• This role is currently working onsite and is expected to work onsite for the majority of working hours. The primary work location for this role is 700 Dexter Ave N., with flexibility to work remotely on a limited basis. We are a Washington State employer; any remote work must be performed in Washington State

Travel

• The successful applicant may be invited to attend occasional national and international conferences

Additional Comments

• **Please note, this opportunity offers relocation assistance**
• **Please note, this opportunity may offer work visa sponsorship**

Annualized Salary Range

• $86,150 - $106,650

* Final salary depends on required education for the role, experience, and level of skills relevant to the role, along with work location, where applicable.

Benefits

• Employees (and their families) are eligible to enroll in benefits per eligibility rules outlined in the Allen Institute’s Benefits Guide. These benefits include medical, dental, vision, and basic life insurance. Employees are also eligible to enroll in the Allen Institute’s 401k plan. Paid time off is also available as outlined in the Allen Institute’s Benefits Guide. Details on the Allen Institute’s benefits offering are located at the following link to the Benefits Guide: https://alleninstitute.org/careers/benefits.

It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities.