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Lawrence Livermore National Laboratory · 1 week ago

Computational Bioengineer - Postdoctoral Researcher

Livermore, CA

Full-time

Onsite

Senior Level

$118K/yr - $135K/yr

Lawrence Livermore National Laboratory (LLNL) is seeking a highly motivated Postdoctoral Researcher to conduct research in protein engineering for biomaterials, focusing on machine learning-driven computational pipelines for protein and polymer design. The role involves collaborating with interdisciplinary teams, developing ML-based approaches, and publishing research findings.

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Growth Opportunities

No H1B

U.S. Citizen Only

Responsibilities

Conduct advanced independent research, designing, analyzing, and extending ML-based tools (including large language model-based) for design and optimization of intrinsically disordered proteins (IDPs) and polymers

Participate in the development of protein design computational frameworks and analysis tools

Collaborate with external partners (Universities, Industry, other National Laboratories) to advance computational biology simulation efforts

Prepare complex and detailed progress reports, written analyses, and verbal briefings to support project needs and deadlines and to present research results to sponsors

Independently pursue the development of new and innovative research methods relevant to the needs of Laboratory programs and/or external funding agencies

Contribute to proposals and statements of work

Publish research results in peer-reviewed scientific or technical journals and present results at external conferences, seminars, and/or technical meetings

Travel as needed to coordinate with research collaborators and to attend external meetings and conferences

Perform other duties as assigned

Qualification

Machine LearningProtein EngineeringDeep LearningPythonComputational BiologyBioinformaticsHigh-Performance ComputingIndependent ResearchCollaborationCommunication Skills

Required

PhD in Machine Learning, Computational Biology, Statistics, Computer Science, Mathematics or a related technical or scientific field, or the equivalent combination of education and related experience

Fundamental knowledge and/or experience developing and applying algorithms in several of the following ML areas/tasks: protein sequence to function ML, polymer design ML, deep learning, unsupervised feature learning, zero- or few-shot learning, active learning, transformer-based language modeling, multimodal learning, ensemble methods

Experience developing and implementing deep learning models and algorithms using modern software libraries such as PyTorch, TensorFlow, or similar as evidenced through publications or software releases

Experience working with proteins and polymers, and domain knowledge in bioinformatics and protein structure modeling sufficient to communicate effectively with team members

Ability to work independently on defined research projects, as well as a member of a team with a diverse set of scientists, engineers, and other technical and administrative staff

Computer skills including programming experience with Python, or C++, and expertise with the UNIX and high-performance computing environments

Ability to develop independent research projects as demonstrated through publication of peer-reviewed manuscripts

Ability to travel as necessary

Preferred

Strong understanding of protein bioinformatics and/or protein function prediction

Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations of complex workflow

Experience in collaborating with experimental biologists