Machine Learning; ML Bioengineer

Position: Machine Learning (ML) Bioengineer
Company Description

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

Job Description

Wehave an opening for a Machine Learning (ML) Bioengineer to conduct research training and evaluating next-generation clinical, protein and genome language models. You will join the Bioresilience Incubator, a dynamic engineering center that integrates predictive computational modeling, machine learning, and experimental biology to advance national security and public health missions. This position will be in the Computational Engineering Division (CED), within the Engineering Directorate, matrixed to the Bioresilience Incubator.

As a member of our multidisciplinary team, you will collaborate with experts in machine learning, molecular simulation, optimization, and bioinformatics, and interface with experimentalists generating large datasets via novel high-throughput assays. You will leverage in-house computational tools and contribute to the design, training, and evaluation of new machine learning-based methods.

Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.

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 to develop, implement, and evaluate computational frameworks and models.
• Contribute to the development and application of advanced analysis methodologies; analyze data; document research through presentations and peer-reviewed publications.
• Support technical activities for new capability development and provide solutions to moderately complex to complex technical problems using established and innovative methods.
• Contribute to the completion of project milestones, influencing the development of organizational goals and objectives. Establish, implement, and maintain quality standards for project deliverables.
• Contribute to briefings and presentations documenting project activities and research results.
• Routinely interact with technical contacts at sponsor and partner organizations; represent the organization on specific technical projects.
• Participate in the development of future research directions and proposals to secure ongoing projects in computational protein design.
• Balance multiple projects/tasks and priorities to ensure deadlines are met, working independently with minimal direction within the scope of assignments.
• Perform other duties as assigned.

Additional job responsibilities, at the SES.
3 level

• Determine, propose, and implement advanced analysis methodologies and contribute to identifying future research directions and proposals that will secure future projects in the field.
• Guide the completion of projects and influence the development of organizational goals and objectives.
• Lead the development of briefings and presentations documenting to project activities and research results.
• Represent the organization as the primary technical contact on tasks and projects, serving on internal technical/advisory committees and potentially on external committees.
• Oversee the activities of other personnel, providing informal mentoring and guidance to less-experienced team members.
• Contribute to and influence the development of innovative projects, principles, and ideas in computational protein design.

Qualifications

• Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
• Master's degree in Machine Learning, Computational Biology, Statistics, Computer Science, Mathematics, or a related 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 using modern software libraries such as PyTorch, Tensor Flow, or similar, as evidenced by publications or software releases.
• Experience with high-performance computing, multi-node, multi-GPU, distributed training.
• Comprehensive knowledge in protein and genome language models sufficient to communicate effectively with team members and subject matter experts.
• Proficient…