The B.I.O.N.I.C. Lab in the Department of Bioengineering at the University of Pittsburgh supported by three funded NIH R01s, an NSF grant, an R44, and two NIH R21 and has multiple positions (Postdoc, Technician, and Graduate Student).
See an interview that discusses the group philosophy: https://www.skrapsofbrilliance.com/podcast/episode/4d6c3071/the-fit-and-the-furious-tk-kozai-from-lab-life-to-oh-no-he-didnt
The goals of the lab broadly fall into three categories:
(1) Manipulation of neuronal and non-neuronal cells to influence the function of neuronal networks, and understanding how to read from or write to the brain, (especially understanding what information is "lost-in-translation" between the brain and the interface),
(2) Improving long-term performance of implanted electrodes and integrating man-made (engineered) technology with the human brain for the purpose of studying normal and injured/diseased nervous systems in vivo at the cellular level, as well as restoring function to patients,
(3) Understanding the role of neuroimmune cells in neuronal damage and regeneration, and using engineering approach to understand the mechanisms behind neurodegenerative diseases as well as exploring new treatments. (Multiple Sclerosis, Alzheimer's, Autism)
Desired skillsets include proficiency in in vivo multiphoton microscopy or electrophysiology.
For Postdoctoral Candidates, he/she should possess a Ph.D. degree in a related field including but not limited to Biomedical Engineering, Neurobiology, Neuroscience, Molecular/Cellular Biology, Electrical Engineering, Computer Science, Physics, Optics, Material Science, and Mathematics. Animal surgery experience is preferred. The candidate should have a strong research background in in vivo electrophysiology, or in vivo two-photon microscopy. Expertise with in vivo two photon imaging, viral transduction in rodent brain, image processing (e.g. GCaMP) and head-fixed visual cortex experiments (V1) are desired. Experiences with electrical stimulation, optogenetics, electrochemistry, material characterization, functional/evoked electrophysiology/imaging, electrochemistry, signal processing (ImageJ/Fiji and MATLAB) and analysis of imaging (2-6 dimension) and electrophysiology data, immunohistochemistry, SEM, basic circuits, CAD based programming, FEM, 3D printing, Labview programming, stroke, TBI, and neurodegenerative diseases (MS, Autism, AD/ADRD) are seen as advantages. Successful candidate will work on the chronic neural interface with special focus on implant-tissue interaction. He/she will be working with an interdisciplinary team of neural engineers, neuroscientists, neurosurgeon, biologists, and material scientists. It is expected that most candidates will lack experience in all the above areas; training will be provided to fill necessary proficiencies.
Interested candidates should submit a statement on the alignment of the candidate’s research interest to the lab and relevant research experience, curriculum vitae, the names of three references, and date of availability to Professor Takashi Kozai (firstname.lastname@example.org).
Prospective Graduate Students, should apply here by the December 1st deadline. It is recommended that you select the Neural Engineering Track and contact Professor Takashi Kozai (email@example.com) early. As this is a multidisciplinary lab, we also accept motivated and ambitious candidates with BA/BS or in Graduate Programs of other related majors including, but not limited to: Neurobiology, Neuroscience, Molecular/Cellular Biology, Biochemistry, Chemistry, Electrical Engineering, Computer Science, Mechanical Engineering, Chemical Engineering, Physics, Optics, Material Science, and Mathematics.
Undergraduate Students from all academic options are encouraged to apply. A minimum commitment of 10 hrs/wk in the lab is expected. Please send the lab a resume and a one-page letter stating why you are interested in joining the lab, and what you hope to gain from the experience.
Lab Expectations and Contract, written by students, agreed to by all. Revised 3 times a year.