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What are the career paths in neurolinguistics?

Career paths in neurolinguistics include roles such as research scientist, clinical neuropsychologist, speech-language pathologist, and cognitive neuroscientist. These positions often require advanced degrees like a master's or Ph.D., along with skills in neuroimaging, data analysis, and understanding of language processing in the brain.

Is there a high demand for neuroscientists?

Neuroscientists, including those working on brain-machine interfaces, are in increasing demand due to advancements in neurotechnology and the growing need for research in neural disorders and brain-computer communication. Employment opportunities are expected to grow as interdisciplinary skills in neuroscience, engineering, and data analysis become more valuable in both academia and industry. Certifications in neuroimaging or programming can enhance job prospects in this field.

What are the typical daily responsibilities of someone working in a Brain Machine Interface position?

Professionals in Brain Machine Interface roles usually divide their time between designing experiments, analyzing neural data, developing and testing interface prototypes, and collaborating with cross-disciplinary teams such as neuroscientists, engineers, and clinicians. They may also be involved in writing technical documentation, participating in regulatory compliance activities, and keeping up with the latest scientific literature. Depending on the project, work can flow between laboratory research and computational tasks, requiring flexibility and an eagerness to learn new techniques. The environment is often collaborative and research-focused, providing ample opportunities to contribute to exciting advancements in neurotechnology.

What are the key skills and qualifications needed to thrive in the Brain Machine Interface position, and why are they important?

To thrive in a Brain Machine Interface (BMI) role, you need a strong background in neuroscience, biomedical engineering, computer science, or a related field, often supported by advanced degrees or specialized training. Proficiency with signal processing software (such as MATLAB or Python), brain imaging tools, and hardware prototyping is typically required, along with familiarity with regulatory standards. Strong problem-solving skills, collaboration, and attention to detail help individuals excel in multi-disciplinary teams working at the intersection of biology and technology. These competencies are crucial for developing safe, effective interfaces and driving innovation in this fast-evolving field.

Are BCIs the future?

Brain Machine Interface (BMI) technology is advancing rapidly, with applications in medical rehabilitation, neuroprosthetics, and human-computer interaction. As research progresses, BCIs are expected to become more integrated into healthcare and consumer devices, potentially transforming how humans interact with technology in the future.

What jobs can I get with HCI?

With expertise in Human-Computer Interaction (HCI), you can pursue roles such as UX designer, usability analyst, interaction designer, or research scientist. These jobs often require skills in user-centered design, prototyping tools, and understanding of cognitive psychology or ergonomics.

What is a Brain Machine Interface job?

A Brain Machine Interface (BMI) job involves developing technologies that connect the human brain with computers or external devices. Professionals in this field work on designing, testing, and improving neural interfaces to restore lost sensory or motor functions, enhance cognitive abilities, or enable direct brain communication with machines. Roles may include neuroscientists, engineers, and software developers collaborating to advance BMI applications in healthcare, assistive technology, and neuroprosthetics.

What are the most commonly searched types of Brain Machine Interface jobs in Pennsylvania? The most popular types of Brain Machine Interface jobs in Pennsylvania are:
What are popular job titles related to Brain Machine Interface jobs in Pennsylvania? For Brain Machine Interface jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Brain Machine Interface jobs in Pennsylvania look for? The top searched job categories for Brain Machine Interface jobs in Pennsylvania are:
Brain Machine Interface jobs near you
Infographic showing various Brain Machine Interface job openings in Pennsylvania as of July 2026, with employment types broken down into 4% As Needed, 69% Full Time, 20% Part Time, 1% Temporary, 5% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.
Post Doctoral Associate-B.I.O.N.I.C. Lab

Post Doctoral Associate-B.I.O.N.I.C. Lab

University of Pittsburgh

Pittsburgh, PA • On-site

$47K - $64K/yr

Other

Posted 4 days ago

Job description

The B.I.O.N.I.C. Lab seeks a Post Doctoral Associate to resolve how intracortical microstimulation (ICMS) and next-generation photoresponsive electrodes evoke specific somatosensory and visual percepts, working across the two grant-aligned threads below.

The first thread operationalizes the Bidirectional Translation Framework in Kozai et al., JNE 2026 ("Solving the Problem of Inception"), pairing reverse-translation experiments (ICMS in individuals with spinal cord injury implanted with microelectrode arrays in primary somatosensory cortex during real-time BCI control, with the Gaunt and Collinger groups) with forward-translation experiments in NHP visual cortex (Gharbawie) and mouse visual cortex (Vazquez, Hooks, Kozai), thereby converting human perceptual reports into testable circuit hypotheses and returning optimized stimulation parameters to clinical BCI users.

The second thread, R01 NS105691 (MPI Kozai/Li, NINDS, PO Doe Kumsa), develops untethered boron-doped diamond Wireless Axon microelectrodes (MCD and NCD) that decouple the skull-to-tissue mechanical tether, reducing chronic micromotion-driven inflammation, and that exploit photovoltaic (capacitive) and photothermal stimulation to enhance somatic versus axonal selectivity relative to faradaic ICMS, with chronic in vivo validation in mouse visual cortex via two-photon calcium imaging, intrinsic signal optical imaging, and electrophysiology.

Both threads converge on a single mechanistic question, how spatially patterned current or photonic delivery recruits identified neuronal populations in sensory cortex across acute and chronic timescales, with secondary opportunities to extend the platform to gliomodulation, AD, MS, and neuroinflammation as career-development directions.

Key Responsibilities

  1. Design and execute chronic in vivo ICMS and Wireless Axon photostimulation experiments in mouse visual cortex, combining two-photon calcium and hemodynamic imaging, intrinsic signal optical imaging, Neuropixels and high-density electrophysiology, and slice electrophysiology validation
  2. Contribute to NHP visual cortex ICMS experiments in the Gharbawie lab and to analysis of human somatosensory ICMS datasets in the Gaunt and Collinger groups, building the cross-species comparisons that the Inception framework requires
  3. Characterize boron-doped MCD and NCD diamond electrodes through electrochemistry (CV, EIS, voltage transients), photovoltaic and photothermal benchtop assays, and chronic in vivo biocompatibility, in coordination with the Li Lab (MSU) on device iteration
  4. Quantify how stimulation parameters (waveform, frequency, pulse width, irradiance) map onto cell-type-specific recruitment, mesoscale circuit dynamics, and behavioral or perceptual outcomes across species
  5. Build reproducible multimodal analysis pipelines in MATLAB, Python, and ImageJ or Fiji, with code released alongside publication
  6. Prepare first-author manuscripts, present at SfN, NER, and BRAIN PI meetings, and contribute to renewal and follow-on grant applications
  7. Mentor graduate and undergraduate trainees in surgical, imaging, electrochemical, and computational methods

The postdoc will cross-train across the labs of Robert Gaunt and Jennifer Collinger (human somatosensory BCI), Omar Gharbawie (NHP visual cortex), Alberto Vazquez (mouse visual cortex hemodynamics and two-photon), Bryan "Mac" Hooks (mouse visual and sensorimotor circuits), Chengcheng Huang (computational modeling), and Wen Li (MSU, diamond device fabrication), under the University of Pittsburgh Neural Engineering Cross-Translation (UP NExT) initiative.

Qualifications

Required:

  1. Ph.D. in Bioengineering, Neuroscience, Neurobiology, Biomedical Engineering, Electrical Engineering, Computer Science, Mechanical Engineering, Chemical Engineering, Physics, Optics, Materials Science, Molecular or Cellular Biology, Biochemistry, Chemistry, or Mathematics
  2. Proficiency in signal processing and quantitative analysis in MATLAB, Python, or equivalent, evidenced by first-author publication or shared code
  3. Strong scientific writing and oral communication, with manuscript and conference experience
  4. Ability to work independently and within an interdisciplinary team

Preferred (one or more):

  1. In vivo multiphoton microscopy in visual or sensorimotor cortex, including stereotaxic surgery, chronic cranial window preparation, and AAV delivery
  2. ICMS, optogenetics, or neuromodulation experience, particularly in visual cortex
  3. NHP electrophysiology, NHP visual neuroscience, or analysis of human cortical recording datasets
  4. Electrochemistry (CV, EIS, voltage transient analysis), confocal microscopy, immunohistochemistry, or SEM characterization of neural electrodes
  5. Computational modeling of neural circuits, volume conduction, or stimulation-evoked activation
  6. Familiarity with brain-machine interface paradigms or sensory neuroprosthetic design
  7. Secondary interests in glial biology, neurodegeneration (MS, AD, stroke), or neuroinflammation, as career-development extensions of the primary somatosensory-visual ICMS program

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