Mathematical Algorithms Software Engineer

Berkeley Lab’s CAMERA (Center for Advanced Mathematics for Energy Research Applications) has  immediate opening(s) for a Computer Systems Engineer (CSE) position to develop mathematical algorithms and related software from Applied Mathematics, Computational Sciences and/or Data Science to work on designing Artificial Intelligence and Machine Learning techniques (AI/ML) for the automation of structure analysis from microscopic images coming from one or more instruments, using visible light as well as other wavelengths used for imaging samples of interest to DOE, e.g. infra-red, ultra-violet, X-ray, multispectral, etc., as well as analysis of metadata and other textual information associated to scientific datasets.

In this exciting role, you will combine mathematics, statistics with new machine learning, and automation in support of data science tasks needed within the laboratory, for example, in data management as part of quality control of materials imaged at different facilities within the Berkeley lab and beyond. You will work as part of a collaborative team to integrate sample metrology into quantitative computational models able to predict the outcome of experimental approaches, as well as to evaluate, develop and apply automation solutions to organize these data. You will be working closely with bench scientists, automation engineers and software developers in devising methods for high-throughput data analysis for feedback into experimental design, as part of CAMERA allied to other centers, programs and/or stakeholders. 

The core values of CAMERA reflect a strong commitment to diversity, equity, and inclusion. We seek candidates who will support a culture in which the entire CAMERA community feels welcomed and valued. An ongoing commitment to recruiting a vibrant, diverse and talented workforce is paramount to promoting a diverse lab community.

What You Will Do:

• The CSE will join in the design, development, and optimizations of AI/ML data driven models.
• Develop quantitative predictive models based on scientific data sets of DOE interest, including code documentation and testing before incorporation into deployed modules and/or equipment.
• Lead a focused effort to enhance data acquisition and management frameworks, query processed and analyzed data, access data from multiple instruments and facilities in a unified way and relate these data to one another in support of multi-modal analyses.
• Use machine-learning approaches to predict outcomes based on scientific data using state-of-the-art computing infrastructure, e.g., NERSC, cloud, etc.
• Work closely with CAMERA scientists and engineers to deploy and evaluate the software, as well as participate in writing scientific papers to conferences and journals.
• Provide training to colleagues and write excellent documentation, to elevate the work from a proof of concept to maintainable, long-lasting infrastructure.
• Develop ML models that take data from a variety of sources to promote materials discovery and plant analysis.
• Work on and resolve problems of diverse scope where analysis of data requires evaluation of identifiable factors.
• Demonstrate good judgment in selecting methods and techniques for obtaining solutions.
• Network with senior internal and external personnel in their own area of expertise.

What is Required:

• Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 3 years and a Master’s degree; or equivalent work experience.
• Experience and a strong interest in scientific software development or research software engineering.
• Experience using the open-source scientific Python software stack for data analysis, and ability to deploy reusable software components to public repositories.
• Demonstrated record of scientific excellence through publications, talks, talks, or software deliverables.
• Demonstrated knowledge of AI/ML/DL principles and practices, and familiarity with widely-used AI/ML libraries such as scikit-learn, PyTorch, and TensorFlow as well as version control platforms such as Git.
• Experience contributing to a scientific software project in a team environment, which might include co- developing an internal project or contributing to community-based open-source software.
• Experience in developing new mathematical algorithms for data science workflows, data-driven analysis, statistical models, computer vision and/or image processing, including significant expertise in algorithmic development in scientific data and metadata processing from files coming from microscopy and/or simulated/AI-generated image files.
• Demonstrated expertise at successfully working in multidisciplinary teams. In particular, demonstrated expertise in coordinating software development teams.
• Experience in developing open-source code in areas such as text mining, topic modeling, quantitative microscopy, data management, and/or visualization.
• Significant experience with the Scientific Python software stack, including experience in using AI/ML/DL as well as Computer Vision packages.
• Familiarity with software version control systems (git, github, bitbucket) and automated documentation systems (sphinx etc.).
• Ability to interact with a variety of technical and scientific personnel including Research Associates, Scientists and Software Engineers with varying academic backgrounds.
• Strong written and verbal communication skills to present and disseminate scientific software developments at group meetings and conferences.
• Ability to troubleshoot and solve problems of diverse scope where analysis of data requires evaluation of identifiable factors.
• Ability to network with senior internal and external personnel in their own area of expertise.
• Demonstrated ability to work effectively as part of a cross-disciplinary team.

Desired Qualifications:

• Experience in computer vision applied to robotic image acquisition.
• Contributions to open-source scientific software projects.
• Experience creating statistical data analysis methods and procedures.
• Demonstrated record in collaborative software development, especially in distributed teams.
• Experience in data acquisition and analysis of micrographies.
• Experience in data management, including databases.

Want to learn more about Berkeley Lab's Culture, Benefits and answers to FAQs? Please visit: https://recruiting.lbl.gov/

Notes:

• This is a full-time, 1 year, term appointment with the possibility of extension or conversion to Career appointment based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.
• This full salary range of this position is between $8,883 to $14,990 per month and is expected to pay between a targeted range of $9,992 to $12,215 per month depending upon candidates' full skills, knowledge, and abilities, including education, certifications, and years of experience.
• This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
• This position is eligible for remote work. Remote workers are defined as individuals that reside in the United States, but 150 miles away from Berkeley Lab. There may be an expectation to intermittently conduct work, attend meetings and training on site at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.  Work schedules are dependent on business needs.

Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA) and strives to continue building community with these shared values and commitments. Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from women, minorities, veterans, and all who would contribute to the Lab's mission of leading scientific discovery, inclusion, and professionalism. In support of our diverse global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.

Equal Opportunity and IDEA Information Links:Know your rights, click here for the supplement: Equal Employment Opportunity is the Law and the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4.