Afference

Afference

Research Scientist

Cleveland, OH

Sponsorship not specified$134k-$202kDetected 61 days ago
Product ManagementResearchLeadershipCommunicationProblem SolvingMentoringPublic Speaking

About the role

  • This position is vital to maintaining the company's leadership through rigorous and innovative research.
  • What You'll Need for This Position Education PhD in Biomedical Engineering, Neural Engineering, Sensory Neuroscience, Phenomenology, Human Behavior, Human-Product Interaction, or a related field.
  • What's in It for You Work closely with cutting-edge technology.

Responsibilities

  • Lead and design complex experimental programs to test hypotheses that advance our understanding of neural interfacing and neuromodulation technologies.
  • Collaborate cross-functionally with internal teams across research, product development, and engineering to align research objectives with company goals.
  • Manage and oversee research associate staff in their day-to-day experimental work, ensuring high-quality scientific outcomes.
  • The Research Scientist leads advanced research in wearable neural interface technology and neurosensory experiences.
  • This role requires expertise in neural engineering, sensory neuroscience, or related fields to design experiments that drive product innovation.
  • The scientist applies knowledge from biomedical and human-technology sciences, oversees research staff, and collaborates across teams to align research with company goals.
  • We strive to create an intellectually stimulating and collegial working environment.

Requirements

  • Experience with translational science and human trials is highly valued.
  • Familiarity with emerging technologies in neural interfaces and sensory neuroscience is highly desirable.
  • Strong ability to make sound, evidence-based decisions within complex and high-stakes research environments.
  • Ability to work independently while maintaining clear communication and alignment with cross-functional teams and leadership.

Nice to have

  • Experience in translational research, particularly involving neural technology and/or human trials, is strongly preferred.
  • 3+ years of postdoctoral or industry research experience preferred but recent graduates with relevant expertise are welcome.

Skills

  • Strong leadership and mentoring skills, with experience managing research staff or teams.
  • Excellent communication skills, capable of presenting complex scientific concepts to technical and non-technical audiences.
  • Advanced problem-solving skills to identify, mitigate, and prevent errors that could jeopardize scientific outcomes or business viability.

Compensation

  • Afference is committed to providing the sense of touch for the evolution of the human connection to technology and the future of the digital experience.
  • We are leading this effort through deep science and technology, which provides unique experiences compared to classical haptic technologies.
  • Our lean team of experts demands a high level of excellence but can compensate with the commensurate upside potential of an early-growth startup in a high-growth sector of extended reality.
  • Compensation offers depend on skills, qualifications, and experience, and range between:
  • $134,400 to $201,600 per year at 100% FTE

Benefits

  • Medical, dental vision, life, STD, FSA, additional company perks
  • Equity incentives
  • Self-managed PTO
  • Our energy for inventing, creating, and learning spans work and play: we have regular happy hours, plan field trips, play games, play music, and generally have a good time.

Company info

  • Proven accountability and reliability in managing critical responsibilities that influence company success and longevity.
  • You will be part of a growing team of some of the best neural engineering, sensory physiology, and human experience scientists in the world.
  • We are an early-stage deep tech startup company that requires all members to contribute across the entire business.

This listing is sourced directly from Afference's careers page and normalized into a canonical job model.