Research Software Engineer for Intelligent Experiment Steering

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The Data Science and Systems Integration (DSSI) division at the National Synchrotron Light Source II (NSLS-II) develops scientific software to orchestrate experiments, including control systems, automation, networking, data management, and analysis.

This position is for a 3-year term.

Position Description

Brookhaven National Laboratory is seeking a Research Software Engineer / Data Scientist to join the Data Science and Systems Integration (DSSI) Division at the National Synchrotron Light Source-II (NSLS-II). This unique position is jointly supported by two major initiatives: ILLUMINE, a DOE-wide collaboration advancing intelligent experiment steering, and the Quantum-Enhanced Microscopy (QEM) project, which develops next-generation event-based detector and analysis capabilities.

The successful candidate will split their effort between these two efforts, contributing to the development of cutting-edge software infrastructure that powers both intelligent beamline control and quantum-enhanced experimental methods. On the ILLUMINE side, you will help build critical technologies for self-driving beamlines by integrating AI-driven decision-making directly into experimental workflows, accelerating scientific discovery across all six DOE light and neutron sources. On the QEM side, you will advance detector integration, scalable data analysis, and real-time pipelines for novel event-based detectors such as Timepix, with emphasis on GPU-accelerated methods and integration into the Bluesky/Tiled data ecosystem.

This role offers an outstanding opportunity to work at the intersection of artificial intelligence, high-performance scientific software, and advanced x-ray/quantum imaging. The position combines fundamental software engineering, AI/ML integration, and real-time data systems with direct impact on beamline operations and user science at NSLS-II and across the DOE complex.

Essential Duties and Responsibilities:

• Develop, deploy, and maintain open-source software for experiment planning, control, and data acquisition within the Bluesky/Tiled ecosystem.

• Advance detector integration and real-time analysis capabilities, with emphasis on event-based detectors (e.g., Timepix), GPU-accelerated methods, and scalable pipelines.

• Collaborate with scientists and engineers to integrate AI algorithms into beamline operations and enable intelligent experiment steering.

• Design and support automated workflows for calibration, data conversion, and large-scale analysis in operational scientific environments.

• Provide user-facing support, training, and documentation while publishing and presenting results to the broader community.

Required Knowledge, Skills, and Abilities:

• Requires a bachelor's degree in an engineering discipline or closely related field of study. This is an entry level position where formal work experience is not a requirement.

• Proficiency in Python or C++ programming.

• Strong interpersonal and communication skills, with the ability to work effectively in a collaborative research environment.

• Self-motivated, with a strong ability to learn quickly and adapt to new challenges.

Preferred Knowledge, Skills, and Abilities:

• A Bachelor's degree in an engineering discipline or closely related field of study.

• Minimum three (3) years progressively responsible related work experience is required.

• Maintains a sound knowledge of current principles and practices in a specialized engineering field.

• Experience with high-volume scientific data collection, management, and analysis.

• Experience managing distributed software systems.

• Contributions to community-led open-source projects.

• Familiarity with data acquisition and analysis at a synchrotron light source, neutron source, or other major scientific facility.

• Experience in developing and deploying AI models.

• Demonstrated ability to collaborate on distributed software development teams.

• Experience with HTTP APIs, Microservices, and containerization technologies (e.g., Docker, Kubernetes).

• Familiarity with message bus solutions such as Kafka, RabbitMQ, Redis, or ZeroMQ.

Environmental, Health & Safety Requirements