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Assistant Neurotechnology Jobs (NOW HIRING)

Beacon Biosignals

Algorithm Engineer

... and assist them in utilizing algorithms for client engagement. • Support the client-facing ... Beacon Biosignals is a neurotechnology company that brings precision neuroscience into clinical ...

Duke University

POSTDOCTORAL ASSOCIATE

Durham, NC

Mentor and supervise graduate students, research assistants, and technicians. Stay current with developments in cognitive neuroscience, neurotechnology, and wearable sensing, and integrate new ...

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Assistant Neurotechnology information

What is the difference between Assistant Neurotechnology vs Assistant Biomedical Engineer?

AspectAssistant NeurotechnologyAssistant Biomedical Engineer
Required CredentialsTypically requires a bachelor's degree in neuroscience, biomedical engineering, or related fieldsRequires a bachelor's degree in biomedical engineering, bioengineering, or related disciplines
Work EnvironmentResearch labs, neurotechnology companies, healthcare institutionsHospitals, medical device companies, research facilities
Industry UsageFocused on developing and testing neurotech devices and systemsDesigning, testing, and maintaining medical devices and equipment
Common Search & ComparisonOften compared for roles supporting neurotech projects and researchCompared for roles in medical device development and biomedical research

Assistant Neurotechnology and Assistant Biomedical Engineer roles share similar educational backgrounds and work environments, often overlapping in healthcare and research settings. However, Assistant Neurotechnology specializes in neuro-specific devices and systems, while Assistant Biomedical Engineer has a broader focus on various medical devices and equipment.

What are the key skills and qualifications needed to thrive as an Assistant Neurotechnology, and why are they important?

To thrive as an Assistant Neurotechnology, you generally need a background in neuroscience, biomedical engineering, or a related field, often supported by a relevant degree or certification. Familiarity with neuroimaging tools, data analysis software like MATLAB or Python, and laboratory equipment is typically required. Strong attention to detail, teamwork, and effective communication are vital soft skills for collaborating with researchers and clinicians. These skills ensure accurate data collection, smooth research operations, and meaningful contributions to advancements in neurotechnology.

What are some common challenges faced by Assistant Neurotechnology professionals, and how can they be managed effectively?

Assistant Neurotechnology professionals often encounter challenges such as staying current with rapidly evolving technology, managing complex data from neuroimaging or electrophysiological studies, and ensuring accurate, ethical handling of sensitive patient information. To manage these, it's important to engage in continuous learning, maintain strong attention to detail, and collaborate closely with interdisciplinary teams including neurologists, engineers, and researchers. Effective communication and a willingness to seek guidance from senior team members also help in overcoming typical hurdles in this dynamic field.
More about Assistant Neurotechnology jobs
What cities are hiring for Assistant Neurotechnology jobs? Cities with the most Assistant Neurotechnology job openings:
What are the most commonly searched types of Neurotechnology jobs? The most popular types of Neurotechnology jobs are:
What states have the most Assistant Neurotechnology jobs? States with the most job openings for Assistant Neurotechnology jobs include:
What job categories do people searching Assistant Neurotechnology jobs look for? The top searched job categories for Assistant Neurotechnology jobs are:
Assistant Neurotechnology jobs near you
Infographic showing various Assistant Neurotechnology job openings in the United States as of July 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 100% In-person job distribution.
Algorithm Engineer

Algorithm Engineer

Beacon Biosignals

Remote

Full-time

Posted 23 days ago

Job description

Job Summary:
Beacon Biosignals is on a mission to revolutionize precision medicine for the brain, providing an at-home EEG platform for clinical development of novel therapeutics. They are seeking a Machine Learning Engineer to lead the algorithm development lifecycle for medical devices, enhance internal tools, and support client-facing projects.
Responsibilities:
• Participate in and lead the entire biosignal-based algorithm development lifecycle for medical devices including specifications and requirements gathering, data curation and labeling, development, failure-analysis, production, maintenance, and documentation.
• Select, implement, and develop the most appropriate method for each problem, knowing when to apply deep learning techniques and when other methods are more effective.
• Enhance our internal deep learning and machine learning tools to boost team efficiency, introduce new model architectures and algorithmic techniques, and refine the codebase to encourage reusability where needed to enable rapid experimentation.
• Spread and improve our best practices to ensure algorithm implementations are user-friendly, well-documented, and thoroughly tested, including unit tests, comprehensive documentation, CI, and non-regression testing.
• Present results to key stakeholders and assist them in utilizing algorithms for client engagement.
• Support the client-facing projects to understand and shape the impact Beacon algorithms have for our customers, both for existing deployed algorithms, and future algorithm development.
Qualifications:
Required:
• You have more than 4 years of industry experience in machine learning and deep learning, particularly in health sciences or other regulated fields, with a proven track record of bringing algorithms into production.
• You are experienced with digital signal processing (DSP) and statistics and care about using the right tool for the job, which in many cases might not be machine learning or deep learning.
• You are proficient in using PyTorch (preferred) or other deep learning frameworks for training, developing, and deploying deep learning models.
• You are familiar with latest Deep Learning advances (Transformer/ViT, large scale modeling, large model training, ...)
• You follow and adopt best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking.
• You are familiar with biosignals, medical imaging data, or large time-series datasets, or are enthusiastic about learning more in the domain.
• You thrive in a team environment, recognizing that collaboration, open communication, and continuous feedback are essential for collective success.
• You are able to distill, discuss, and present complex technical topics in a way that is appropriate for the audience at hand, both internally and externally.
• You are excited to participate in the entire algorithm development lifecycle, which spans scoping, data wrangling, algorithm development/experimentation, formal validation, quality/regulatory documentation, production deployment, and working with clients who might benefit from these algorithms.
Preferred:
• You are proficient in using PyTorch (preferred) or other deep learning frameworks for training, developing, and deploying deep learning models.
Company:
Beacon Biosignals is a neurotechnology company that brings precision neuroscience into clinical trials and treatments. Founded in 2019, the company is headquartered in Boston, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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