Job Description:
We are seeking a Postdoctoral Researcher Computational Biologist to join a dynamic, multidisciplinary project team focused on in silico design and evaluation of microbial gene and protein sequences. You will perform work in an exciting R&D environment in support of a program that integrates bioinformatics, machine learning, structural modeling, software engineering, and large experimental datasets to enable computational protein design. While supporting applied research projects, you will be provided mentorship, practical training, and skill development to develop depth and breadth in machine learning techniques as well as gain exposure to a variety of application areas. This position is in the Systems and Synthetic Biology group in the Biosciences and Biotechnology Division.In this role you will - Collaborate with researchers in protein engineering, structural modeling, bioinformatics, software engineering, and High Performance Computing
- Develop bioinformatics tools and software that enable experimental data integration, protein sequence design, and high-density encoding of synthetic functions in microorganisms
- Inform the acquisition of and leverage large experimental datasets to enable AI-enabled protein design and functional assessment
- Carry out development of moderately complex data analysis algorithms to address bioinformatics needs
- Design technical solutions with limited direction, participating as a member of a multidisciplinary team to design/implement software and perform data analysis
- Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
- Collaborate with others in a multidisciplinary team environment and other national laboratories and industry to accomplish research goals.
- Publish research results in peer-reviewed scientific or technical journals and present results at external conferences seminars and/or technical meetings.
- Perform other duties as assigned.
Qualifications
- Ph.D. in Bioinformatics, Computational Biology, Computer Science, Engineering, or another technical discipline providing an underlying skillset in data analysis, bioinformatics, and machine learning techniques
- Comprehensive knowledge of one or more of the following: scientific data analysis, statistical analysis, data management technologies, protein structure analysis, protein structure modeling, homology modeling, and protein engineering
- Experience developing and/or applying new bioinformatics software tools and workflow/pipelines to solve problems in computational protein analysis
- Experience with bioinformatic analysis of experimental data in molecular biology
- Broad experience developing software with Python, R, Julie, C, or C++
- Proficient verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information
- Demonstrated ability to undertake original research and communicate findings in peer-reviewed publications.
Qualifications we desire - Fundamental knowledge of and/or experience developing and applying algorithms in learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, and/or statistical modeling and inference methods
- Experience working with and analyzing next-generation sequencing (NGS) data derived from large variant libraries
- Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform research decisions
Additional Information
All your information will be kept confidential according to EEO guidelines.Position Information This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.
Why Lawrence Livermore National Laboratory? - Included in 2022 Best Places to Work by Glassdoor!
- Flexible Benefits Package
- 401(k)
- Education Assistance
- Flexible schedules (*depending on project needs)
|
