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Mid Level Neuromorphic Computing Jobs in Virginia

Mid-Level Network Engineer At Bcore, our strength comes from how we deliver impact to the mission ... Enterprise Computing Engineering services include modern application technology with containerized ...

Job Title Mid-Level Engineer Location Arlington, VA 22217 US (Primary) Job Type Full-Time Education ... Control, Computing, Communications, Cyber, Intelligence, Surveillance, Reconnaissance, and ...

Envisioneering, Inc. is seeking a Mid-Level Engineer to support the Office of Naval Research (ONR ... Control, Computing, Communications, Cyber, Intelligence, Surveillance, Reconnaissance, and ...

The Mid-Level Technical Analyst analyzes technical information and aligns it to the business ... computing, geographic information systems (GIS), business intelligence (BI) systems, data ...

Data Architect (Mid-Level)

Vienna, VA · On-site

$135K - $155K/yr

We are seeking a skilled Data Architect (Mid-Level) to support operations and sustainment of the ... Scripting and automation in large-scale computing environments. * Strong working knowledge of ...

Data Architect (Mid-Level)

Vienna, VA · On-site

$135K - $155K/yr

We are seeking a skilled Data Architect (Mid-Level) to support operations and sustainment of the ... Scripting and automation in large-scale computing environments. * Strong working knowledge of ...

We are seeking a skilled Data Architect (Mid-Level) to support operations and sustainment of the ... Scripting and automation in large-scale computing environments. * Strong working knowledge of ...

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Mid Level Neuromorphic Computing information

What are the key skills and qualifications needed to thrive as a Mid Level Neuromorphic Computing Engineer, and why are they important?

To thrive as a Mid Level Neuromorphic Computing Engineer, you need a solid background in computer engineering, neuroscience, and machine learning, usually supported by a relevant degree and experience with neural network architectures. Familiarity with tools like Python, MATLAB, TensorFlow, and simulation platforms such as NEST or SpiNNaker, along with knowledge of specialized hardware, is typically required. Strong problem-solving, collaboration, and communication skills help you innovate and effectively share complex ideas with multidisciplinary teams. These skills and qualifications are crucial for developing advanced neuromorphic systems that bridge neuroscience and AI, pushing the boundaries of efficient computing.

What are some common challenges faced by professionals in mid-level neuromorphic computing roles, and how can they be addressed?

Professionals in mid-level neuromorphic computing roles often encounter challenges such as integrating novel hardware with existing software systems, managing the complexity of neural-inspired algorithms, and keeping pace with rapid advancements in the field. Collaborating closely with multidisciplinary teams—including hardware engineers, data scientists, and neuroscientists—can help address these challenges. Additionally, staying updated on the latest research and industry trends, as well as participating in collaborative projects, can enhance problem-solving skills and foster innovation in this evolving area.

What are mid level neuromorphic computing professionals?

Mid level neuromorphic computing professionals are specialists with several years of experience who design, develop, and optimize hardware and software systems inspired by the structure and function of the human brain. They typically work on building and programming neuromorphic chips, developing algorithms that mimic neural processes, and integrating these systems into real-world applications such as robotics or edge computing. Their expertise bridges neuroscience, computer engineering, and artificial intelligence, and they often collaborate with interdisciplinary teams to advance brain-inspired computing technologies.

What is the difference between Mid Level Neuromorphic Computing vs Mid Level Machine Learning Engineer?

AspectMid Level Neuromorphic ComputingMid Level Machine Learning Engineer
Required CredentialsBachelor's in Computer Science, Electrical Engineering, or related field; knowledge of neuromorphic hardwareBachelor's in Computer Science, Data Science, or related; experience with ML frameworks
Work EnvironmentResearch labs, hardware development, AI hardware companiesTech companies, startups, data-driven organizations
Industry UsageAI hardware, neuromorphic chip design, cognitive computingSoftware development, AI applications, data analysis

Mid Level Neuromorphic Computing professionals focus on hardware and cognitive architectures inspired by the brain, often working with specialized hardware and research teams. In contrast, Mid Level Machine Learning Engineers develop algorithms and models primarily in software to solve data-driven problems. Both roles require a strong technical background but differ in their focus on hardware versus software applications.

What are the most commonly searched types of Neuromorphic Computing jobs in Virginia? The most popular types of Neuromorphic Computing jobs in Virginia are:
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Post-Doctoral Researcher - Silicon Photonics for Computing Applications

USC Gould School of Law

Arlington, VA • Hybrid

$80K - $90K/yr

Full-time

Posted 8 days ago


Job description

The Application Specific Intelligent Computing (ASIC) Lab at USC's Information Sciences Institute (USC's ISI) invites applications for a post-doctoral position in Silicon Photonics, with a focus on advanced computing applications.

The selected candidate will contribute to the design, prototyping, and testing of photonic devices and circuits aimed at enabling next-generation computing architectures, such as optical in-memory computing. The role involves close collaboration with leading fabrication partners (e.g., GlobalFoundries, AIM Photonics), participation in multi-project wafer (MPW) tapeouts, and system-level experimental validation of fabricated prototypes. A strong drive for innovation is essential, as the work will push the boundaries of current photonic technologies and computing models.

**This is a one year appointment, with possibility of extension based on project funding and performance.**

**This position is located in our Arlington, Virginia Office. Hybrid work option available.**

Responsibilities

  • Lead photonic integrated circuit (PIC) design and simulation using commercial tools.
  • Contribute to novel photonic computing architectures including optical in-memory and neuromorphic computing.
  • Coordinate tapeout and fabrication of silicon photonic devices with commercial foundries.
  • Characterize fabricated devices using optical and electrical test setups.
  • Collaborate with interdisciplinary teams and external partners for end-to-end prototyping and validation.
  • Contribute to publications, technical reports, and intellectual property development.

Qualifications

  • Ph.D. in Electrical Engineering, Physics, Photonics, or a closely related field.
  • Strong background in Integrated Phonics, including demonstrated experience in PIC design, layout, and tapeout in commercial foundries.
  • Proficiency with photonic design and simulation tools (e.g., Lumerical, IPKISS, Ansys, KLayout).
  • Hands-on experience in device fabrication, testing, and characterization (e.g., using probe stations, tunable lasers, optical spectrum analyzers).
  • Familiarity with materials such as Si, SiN, AlN, BaTiO, or 2D materials is a plus.
  • Strong publication record and excellent communication skills.
  • Ability to work independently and collaboratively in a multidisciplinary research environment.

Preferred Experience

  • Experience with MPW runs (e.g., AIM Photonics, GF Fotonix).
  • Exposure to optical in-memory compute or optical AI accelerators.
  • Familiarity with advanced packaging methods for photonics.
  • Previous collaboration with industry or transition of research to commercial applications.

Why Join Us

This position offers the opportunity to contribute to cutting-edge research in photonics-enabled hardware acceleration for AI and advanced computing. You will work alongside a dynamic team at the forefront of next-generation system design, engaging in real-world prototyping with direct impact on future computing platforms.

The role provides hands-on collaboration with top-tier fabrication partners and national research consortia, access to advanced prototyping infrastructure, and the chance to shape the direction of innovative silicon photonics technologies. It is an ideal opportunity for those passionate about bridging fundamental research with practical, scalable solutions.

The annual base salary range for this position is $80,000 - $90,000. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, federal, state and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.

Minimum Education: Ph.D. or equivalent doctorate within previous three years
Minimum Experience: 0-1 year
Minimum Field of Expertise: Directly related education in research specialization with advanced knowledge of equipment, procedures and analysis methods.

USC is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other characteristic protected by law or USC policy. USC observes affirmative action obligations consistent with state and federal law. USC will consider for employment all qualified applicants with criminal records in a manner consistent with applicable laws and regulations, including the Los Angeles County Fair Chance Ordinance for employers and the Fair Chance Initiative for Hiring Ordinance, and with due consideration for patient and student safety. Please refer to theBackground Screening Policy Appendix Dfor specific employment screen implications for the position for which you are applying.

We provide reasonable accommodations to applicants and employees with disabilities. Applicants with questions about access or requiring a reasonable accommodation for any part of the application or hiring process should contact USC Human Resources by phone at (213) 821-8100, or by email atuschr@usc.edu. Inquiries will be treated as confidential to the extent permitted by law.

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