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Neuromorphic Computing Research Jobs (NOW HIRING)

VP of Optics

San Jose, CA · On-site

$325K - $400K/yr

You will lead an elite team of engineers to translate groundbreaking research into robust, market ... Experience with neuromorphic computing or advanced AI hardware architectures. * Knowledge of ...

Post Doctoral Research Fellow

Boise, ID · On-site

$46K - $63K/yr

Publish high-impact research in top-tier neuromorphic engineering, circuit design, and/or computing journals and conferences. * Collaboration: Work closely with materials teams in AWESOME Subprojects ...

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How much do neuromorphic computing research jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for neuromorphic computing research in the United States is $22.22, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $23.80 per hour, depending on experience, location, and employer.

What is neuromorphic computing research?

Neuromorphic computing research is the study and development of computer systems inspired by the structure and function of the human brain. Researchers in this field design hardware and software that mimic neural architectures, aiming to achieve greater efficiency and adaptability than traditional computing methods. This research often involves creating artificial neurons and synapses using novel materials and architectures to enable advanced tasks like pattern recognition and real-time learning. The ultimate goal is to create energy-efficient, intelligent computing systems for applications ranging from robotics to AI and sensory processing.

What are some common challenges faced by professionals working in neuromorphic computing research?

Professionals in neuromorphic computing research often encounter challenges related to the interdisciplinary nature of the field, requiring deep knowledge of neuroscience, computer engineering, and machine learning. Developing hardware that effectively mimics neural architectures can be complex due to limitations in current fabrication technologies and the need for novel algorithms. Additionally, researchers must frequently collaborate with teams from diverse backgrounds, which necessitates strong communication and adaptability. Securing funding and staying updated with rapid advancements in both neuroscience and AI are also ongoing challenges in this dynamic research area.

What are the key skills and qualifications needed to thrive in Neuromorphic Computing Research, and why are they important?

To thrive in Neuromorphic Computing Research, a strong background in computer science, electrical engineering, neuroscience, and mathematics—often at the graduate level—is essential. Familiarity with programming languages (such as Python or C++), neural network frameworks, hardware description languages, and simulation tools like SpiNNaker or NEST, as well as published research experience, is typically required. Critical thinking, creativity, interdisciplinary collaboration, and effective communication set outstanding researchers apart in this evolving field. These skills and qualities are crucial for driving innovation and bridging the gap between biological intelligence and artificial computing systems.
More about Neuromorphic Computing Research jobs
What cities are hiring for Neuromorphic Computing Research jobs? Cities with the most Neuromorphic Computing Research job openings:
What states have the most Neuromorphic Computing Research jobs? States with the most job openings for Neuromorphic Computing Research jobs include:
Principal Engineer for Geospatial Computing Infrastructure

Principal Engineer for Geospatial Computing Infrastructure

Oak Ridge National Laboratory

Oak Ridge, TN • On-site

Full-time

Posted 5 days ago


Oak Ridge National Laboratory rating

9.3

Company rating: 9.3 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

4th of 103 rated laboratories


Job description

Job Summary:
Oak Ridge National Laboratory is a U.S. Department of Energy national laboratory with a mission to address the nation’s pressing challenges. The Principal Engineer for Geospatial Computing Infrastructure will lead the formation of a Geospatial Data Center, overseeing its strategic direction, operational management, and team building to support advanced geospatial high-performance computing research.
Responsibilities:
• Develop and refine a strategic roadmap for the GDC, including defining its mission, vision, value proposition, operating model (services, research, partnerships), business case, metrics of success and growth path.
• Oversee the effective integration, operation, scaling and optimization of the GDC’s compute, storage, networking and geospatial-data assets (existing and planned). Ensure high performance, high availability, cost-effectiveness, data integrity, and operational resilience.
• Define, implement and continually improve service offerings (e.g., large-scale geospatial compute pipelines, data ingest/curation/archive, analytics/visualization, user support). Establish operating policies, SLAs, user workflows, resource allocation models and performance metrics.
• Cultivate and lead a research-oriented culture within the center: identify and integrate emerging geospatial/HPC technologies (e.g., ML Ops for geospatial data, real-time analytics, cloud/HPC hybrid, edge geospatial compute, neuromorphic, quantum), pilot new capabilities, foster innovation partnerships (academia, industry, federal sponsors). Serve as principal investigator (PI) or co-PI on research proposals, secure external funding, and help shape the center’s research agenda.
• Hire, develop, and lead a highly agile and high-performing multidisciplinary team covering, HPC/data infrastructure, data engineering, software engineering, user engagement, and operations. Foster a culture of excellence, collaboration, inclusion and continuous learning.
• Serve as the external interface for the center: liaise with sponsors (DOE, other federal agencies, industry, academia), build and maintain relationships, understand user needs, market the center’s capabilities, co-develop new programs. Internally align with ORNL leadership, HPC facility management, ORNL’s National Center for Computational Sciences, data services groups, programmatic divisions and labs.
• Develop and manage budgets, resource planning (people, infrastructure, capital investments), cost model, vendor and subcontractor relationships. Define governance structures, policies (data governance, security, access), compliance (cybersecurity, data privacy, export controls).
• Define performance metrics and dashboards for the center (e.g., utilization, throughput, time-to-science, user satisfaction, cost per unit, growth of services), regularly report to ORNL leadership, sponsors and stakeholders. Drive continuous improvement and benchmarking against peer organizations.
• Ensure robustness of operations (backup/archival, disaster recovery, continuity), manage risk (data loss, data protection, downtime), oversee infrastructure lifecycle (refresh, decommissioning), and uphold industry best practices in HPC/data center operations.
Qualifications:
Required:
• Advanced degree (MS or PhD) in Computer Science, Data Science, Geospatial Science (GIS/remote sensing), Electrical/Computer Engineering, or a closely related discipline.
• Minimum of 10–12 years of relevant experience (or equivalent) in one or more of the following: geospatial science/engineering, HPC/data center operations, large-scale data infrastructure, research center leadership, service delivery in a technical organization, or related field.
• Proven track record of leadership: building and managing multidisciplinary teams, developing strategy, hiring, mentoring, and managing scientists/engineers/technologists.
• Solid technical expertise across high performance computing (compute, storage, interconnects, networking), large-scale data management (ingest, curation, archive), geospatial data workflows (remote sensing, GIS, mapping, analytics) and infrastructure-as-a-service models.
• Experience with service delivery models (e.g., user support, resource allocation, service catalogue, SLAs) and/or research infrastructure.
• Experience engaging with federal sponsors (e.g., DOE, DoD, other agencies) or large external stakeholders; demonstrated ability to produce proposals, manage programs, and interface at senior levels.
• Strong communication and collaboration skills: able to articulate vision and technical concepts to senior leadership, sponsors, non-technical stakeholders, and users; comfortable representing the center externally.
• Demonstrated financial/acquisition/contract experience: budget planning, vendor/subcontractor management, procurement, cost-modelling, and governance oversight.
• Demonstrated familiarity with data governance, security, compliance (cybersecurity, export controls, access policies) as applies to HPC/data infrastructure in federal research environments.
• Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory.
• Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs.
• HSPD-12 PIV badge: This position requires the ability to obtain and maintain an HSPD-12 PIV badge.
• SCI Clearance: This position requires the ability to obtain and maintain a Sensitive Compartmented Information (SCI) clearance from the Department of Energy.
Preferred:
• Experience specifically in geospatial high-performance computing, e.g., leveraging HPC for remote sensing, large-scale mapping, geospatial analytics, Earth system science, real-time geospatial streaming, or associated research infrastructure.
• Experience leading or being part of a research center or institute (or similar) with a mix of service delivery and research mission.
• Experience with leading edge geospatial/HPC technologies: AI/ML for remote sensing/geospatial, cloud-HPC hybrid architectures, geospatial edge compute, real-time analytics, and geospatial big data platforms.
• Demonstrated success securing external funding and managing the resulting programs.
• Familiarity with ORNL-style national laboratory environment (or similarly complex research institution), federal research stakeholders, user facilities, and large-scale infrastructure operations.
• Established professional network in the geospatial, HPC or data infrastructure community; prior leadership of/participation in geospatial or HPC user communities, etc.
• Prior experience with practices of operationalizing research infrastructure: metrics, service catalogue development, business model transition (from support to mission-driven), and growing a team into a standalone organizational entity.
• Excellent written and oral communication skills.
Company:
Oak Ridge National Laboratory holds a range of R&D assignments, from fundamental nuclear physics to applied R&D on advanced energy systems. Founded in 1943, the company is headquartered in Oak Ridge, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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