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Part Time Machine Learning Neuroscience Jobs (NOW HIRING)

New York University

Research Scholar

New York, NY · On-site

$27.77/hr

Responsibilities include coding and running machine learning experiments, analyzing and ... This is a part time appointment and would require a work schedule of approximately 27 hours per ...

Implicit

AI Engineer (US-Based / Part-Time)

Solid understanding of NLP, machine learning, and modern deep learning techniques. * Hands-on ... Flexible part-time schedule. * Remote work within the United States. * Flexible vacation policy.

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Part Time Machine Learning Neuroscience information

What are the most commonly searched types of Machine Learning Neuroscience jobs? The most popular types of Machine Learning Neuroscience jobs are:
Part Time Machine Learning Neuroscience jobs near you
Senior / Principal Neuromorphic Systems Architect (Cambridge)

Senior / Principal Neuromorphic Systems Architect (Cambridge)

Flagship Pioneering

Cambridge, MA • On-site

$150K - $250K/yr

Part-time

Medical, Retirement

Posted 9 days ago

Job description

Flagship Labs 119 Inc. (FL119) is an early-stage technology company pioneering at the intersection of neuroscience and computation. We build next‑generation technologies to transform how intelligent systems are built and to enable naturalistic, robust intelligence at scale.

The Role

Neuromorphic Systems Architect – responsible for translating nonlinear neural dynamics into next‑generation computational architectures. The role bridges neuroscience, dynamical systems theory, and hardware engineering to design electronic architectures that embody biologically derived principles of computation.

How You Will Contribute
  • Formalize brain‑derived computation using dynamical systems theory and translate these insights into hardware‑relevant abstractions.
  • Architect novel neuromorphic or neuro‑inspired hardware systems (analog, mixed‑signal, in‑memory, or alternative substrates).
  • Define system‑level architecture, including memory models, communication schemes, and energy‑efficient compute primitives.
  • Collaborate with neuroscience, signal processing, and machine learning teams to ensure tight coupling between biological insight and architectural design.
  • Lead feasibility studies, simulations, and early‑stage prototyping efforts.
  • Evaluate trade‑offs across CMOS, emerging devices, photonic, memristive, or other unconventional compute substrates.
  • Contribute to IP strategy, including invention disclosures and patents.
  • Help shape the long‑term compute vision of the company.
Must‑have Qualifications
  • PhD (or equivalent experience) in Electrical Engineering, Applied Physics, Computational Neuroscience, Computer Engineering, or a closely related field.
  • Deep expertise in nonlinear dynamical systems and their application to computation.
  • Experience designing hardware architectures (ASIC, FPGA, analog/mixed‑signal, or emerging device technologies such as RRAM, PCM, memristors, etc.).
  • Strong mathematical foundation in dynamical systems, control theory, or computational modeling.
  • Demonstrated ability to move from theory to implementable system design.
  • 5+ years of relevant research or industry experience (level dependent).
Preferred Experience
  • Prior work in neuromorphic computing or spiking neural network hardware.
  • Experience with event‑driven or asynchronous architectures.
  • Familiarity with reservoir computing, recurrent dynamical systems, or physical computing substrates.
  • Experience working in early‑stage, fast‑paced R&D environments.
  • Track record of patents or high‑impact publications in neuromorphic systems or unconventional computing.
Compensation

Salary range: $150,000 - $250,000. Healthcare coverage, annual incentive program, retirement benefits, and a broad range of other benefits are offered.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

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