Computational Protein Design Scientist

We have an opening for a Computational Protein Design Scientist to conduct research advancing our next-generation machine learning-driven computational pipeline for protein design and optimization of protein-protein interactions. You will join the Center for Predictive Bioresilience (CPB) a dynamic engineering center that integrates predictive computational modeling machine learning and experimental biology to develop medical countermeasures.

As a member of our multidisciplinary team you will collaborate with experts in machine learning molecular simulation optimization and protein structure bioinformatics and interface with experimentalists generating large datasets via novel high-throughput assays. You will leverage in-house computational tools and contribute to the development of new machine learning-based methods for designing and optimizing proteins (e.g. antibodies immunogens) as therapeutics and vaccines. You will also work closely with the ML team to align current capabilities and co-develop a vision for next-generation protein design models and tools. This position will be in the Computational Engineering Division (CED) within the Engineering Directorate.

This position will be filled at either level based on knowledge and related experience as assessed by the responsibilities (outlined below) will be assigned if hired at the higher level.

You will

• Collaborate with project scientists and engineers and participate in developing implementing and evaluating computational frameworks (e.g. LLMs Protein Folding Inverse Folding All-atom structure prediction and design models) optimized for protein design.
• Contribute to and actively participate in the development and application of analysis methodologies analyzing data and documenting research through presentations and peer-reviewed publications.
• Support technical activities for new capability development by providing input recommending enhancements and developing solutions to moderately complex technical problems using established and innovative methods.
• Contribute to the completion of project milestones supporting the fulfillment of organizational goals and objectives.
• Contribute to manuscripts and both informal and formal reports and presentations documenting project activities methods and implementation techniques sequences requirements and research results.
• Assist in establishing implementing reviewing updating and maintaining quality standards for project deliverables.
• Routinely interact with technical contacts at sponsor and partner organizations representing the organization by providing input on specific technical projects.
• Balance multiple projects/tasks and priorities to ensure deadlines are met working independently with limited direction within the scope of assignments.
• Perform other duties as assigned.

Additional job responsibilities at the SES.3 level

• Develop propose and implement advanced analysis methodologies and collaborate with team in identifying future research directions and proposals that will secure future projects in the field.
• Guide the completion of projects by independently determining the appropriate technical objectives criteria and approaches to satisfy and execute project deliverables leading and overseeing the activities of other personnel and providing mentoring to less-experienced team members.
• Represent the organization as the primary technical contact on tasks and projects serving on internal technical/advisory committees sharing relevant knowledge providing opinions and recommendations and exerting influence in developing and achieving project goals.
• Contribute to and influence the development of innovative projects principles and ideas in computational protein design.

Qualifications :

• Masters degree in Machine Learning Computational Biology Statistics Computer Science Mathematics or a related technical field or the equivalent combination of education and related experience.
• Comprehensive knowledge and experience developing and applying algorithms in one or more of the following machine learning areas: deep learning unsupervised feature learning zero- or few-shot learning active learning transformer-based language modeling multimodal learning.
• Experience developing and implementing deep learning models and algorithms and knowledge of and proficiency using modern software libraries such as PyTorch TensorFlow or similar as evidenced by publications or software releases.
• Demonstrated domain knowledge and experience in protein structure machine learning bioinformatics and protein structure modeling sufficient to communicate effectively with team members and subject matter experts.
• Proficient verbal and written communication and interpersonal skills and initiative necessary to work independently collaborate effectively within a multidisciplinary team environment interact with all levels of personnel and present and explain technical information to varied audiences.
• Demonstrated ability to prioritize and balance multiple projects and competing demands while maintaining timely and high-quality standards for deliverables.

Additional qualifications at the SES.3 level 

• Significant experience and advanced knowledge in developing and applying algorithms in advanced machine learning areas developing and implementing medium to large-scale deep learning models and algorithms using modern software libraries and independently developing and executing complex analyses.
• Significant experience and demonstrated ability to lead interdisciplinary teams set clear expectations delegate ensure timely and successful completion of objectives and influence and provide guidance advice and informal mentoring to other personnel and junior team members.
• Demonstrated ability to effectively represent the organization as a primary technical contact share relevant knowledge provide opinions and recommendations exert influence and contribute to the development of innovative projects principles and ideas.

Qualifications We Desire

• PhD in Computational Biology Computational Bioengineering Machine Learning Statistics Computer Science Mathematics or a related field.
• Strong understanding of protein structure bioinformatics and/or protein structure prediction and protein structure datasets.
• Experience with high-performance computing GPU programming parallel programming cloud computing and/or running numerical simulations of complex workflows.
• Experience publishing research results in peer-reviewed scientific journals and presenting at conferences and workshops.

Additional Information :

#LI-Hybrid

Position Information

This is a Flexible Term appointment which is for a definite period not to exceed six years.  If final candidate is a Career Indefinite employee Career Indefinite status may be maintained (should funding allow).

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• 401(k)
• Relocation Assistance
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• Flexible schedules (*depending on project needs)
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  Remote Work :

  No

  
  

  Employment Type :

  Full-time