Computational Neuroscientist

San Francisco /
Engineering /
Full Time
Wispr is building the future of human-computer interfaces controlled by the peripheral nervous system. We're building a team of world class scientists, engineers, and product designers to make that a reality. We're funded by top tier Silicon Valley investors (NEA and 8VC) and backed by angels including Ben Jones (COO, CTRL-Labs), Jose Carmena (Berkeley professor; co-CEO iota), David Gilboa (CEO, Warby Parker), and Will Ahmed (CEO, Whoop). Our founders are Stanford alums and have previously sold a company and run a team at a deep tech startup with over 100M in funding.

We're hiring in SF Bay Area / DC Area / Remote.

As a computational neuroscientist at Wispr, your primary responsibilities will be to design, implement, and improve algorithms to process surface electromyography (EMG) and other neural signals. You will lead experimental design, data collection, and infrastructure development to rapidly iterate on experiments.

Come join us and make magic happen.

Core Job Responsibilities

    • Design and run research/engineering experiments for decoding of speech from electrophysiological signals, such as EMG
    • Rapidly iterate and extend (novel) processing and analysis algorithms
    • Leverage domain knowledge in speech physiology, motor unit action potential decoding, etc., to build scientifically grounded machine learning models
    • Implement data collection frameworks, curate datasets, perform pre-processing/feature extraction, and build machine learning models for EMG decoding
    • Work with electrical engineers and mechanical engineers to propose system design improvements, including custom electrode and filter development
    • In addition to core R&D tasks, develop independent ideas for solving immersive communication and extending non-invasive neural interfaces

Required Knowledge/Skills, Education, And Experience

    • PhD in neuroscience, biomedical engineering, electrical engineering, machine learning, or a closely related discipline
    • 3+ years work experience with neuro-physiological time series data
    • Experience in electrophysiology: EEG, EMG, or intracortical BCI (analysis techniques, de-noising set ups, using multiple data acquisition systems)
    • Published academic research in peer-reviewed journals
    • Ability to produce well-written technical reports and documentation
    • Software engineering skills for machine learning experiments, including experience in Python and packages such as PyTorch or TensorFlow
    • Software engineering best practices, including comfort with Linux environments and git version control
    • Experience working collaboratively with teams

Nice to have Knowledge/Skills, Education, And Experience

    • Expertise in speech physiology or speech decoding
    • Prior work in motor unit action potential decoding from EMG
    • Experience with consumer wearables

Why Wispr?
- Develop cutting edge technologies in a creative and innovative environment.
- Imagine new opportunities in areas that matter and will impact the world you live in.
- Headquarters in an open, green, and bright office in South San Francisco - with a wide view of the bay and proximity to the Caltrain.
- Be a part of a high performing team of the world’s best innovators and executors.
- Receive excellent medical, dental and vision benefits, equity ownership in Wispr and competitive salaries.
- Flexible work arrangements to support you in working in the way that you work best.
- Grow your career and do the best work of your life.

At Wispr, diversity is important to us.

At Wispr, we believe that true innovation starts from people from diverse backgrounds coming together, bridging ideas, and collaborating. Wispr is proud to be an Equal Employment Opportunity employer and is committed to providing an environment of mutual respect where employment opportunities are available to all applicants and teammates without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by applicable law.