Would like to work with brain machine interface in grad school

In summary: Expert summarizerIn summary, the conversation discussed the speaker's plans for graduating from a liberal arts college with a degree in physics and their experience working in behavioral genetics. They expressed interest in brain machine interfaces and mentioned their plan to pursue a PhD in neuroscience with a focus on theoretical neuroscience. The expert summarizer suggests considering a PhD in biomedical engineering or neuroscience with a focus on neural engineering or computational neuroscience as alternative ways to pursue their interests. They also recommend reaching out to professors or researchers for further insights and opportunities.
  • #1
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Hello,

Next year I'll be graduating from a small liberal arts college (University of San Francisco) with a BS in Physics. By that time I'll have 2 years experience working for the Dept of Physiology at UC San Francisco. The experiments I've worked on have been in behavioral genetics, but I personally spend most of my work day coding in MATLAB.

I'm really interested in working with brain machine interfaces in graduate school. Specifically, I'd like to work on transmitting tactile information from prosthetics into the brain. My current best case scenario plan is to pursue my PhD in neuroscience from Columbia University or UC Berkeley with an emphasis on theoretical neuroscience. I'd be interested in hearing alternative ways to pursue my interests at other schools or through other PhD (or even Masters) programs.

Thanks for your time.
 
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  • #2




Congratulations on your upcoming graduation and your experience in the field of behavioral genetics! It sounds like you have a strong background in both physics and coding, which are valuable skills in the field of neuroscience. Your interest in brain machine interfaces and specifically in transmitting tactile information is very exciting and relevant to current research in the field.

One potential option for pursuing your interests in graduate school could be through a PhD program in biomedical engineering. This interdisciplinary field combines principles from engineering, biology, and medicine to develop solutions for medical problems, including brain machine interfaces. Many universities offer PhD programs in biomedical engineering, and some even have specific tracks or concentrations in neuroscience or neural engineering. This could be a great way for you to combine your interests in physics, coding, and neuroscience in a more applied and hands-on approach.

Another option could be to pursue a PhD in neuroscience with a focus on neural engineering or computational neuroscience. These fields also involve the use of coding and theoretical modeling to understand and manipulate brain function, and could provide a strong foundation for your interests in brain machine interfaces. Some potential universities to consider for these programs could be University of Washington, University of Michigan, or University of California San Diego.

Additionally, you may want to consider reaching out to professors or researchers at other universities who are conducting research in brain machine interfaces. They may have insights on different graduate programs or opportunities that align with your interests and goals.

Overall, it seems like you have a strong plan in place for pursuing your interests in graduate school. I wish you all the best in your future academic endeavors and hope that you find a program that allows you to further explore your passion for brain machine interfaces. Good luck!


 

1. What is a brain machine interface (BMI)?

A brain machine interface is a communication system that allows for direct communication between the brain and an external device, such as a computer or prosthetic limb. This is achieved through the use of sensors that detect and interpret brain signals, which are then translated into commands for the external device.

2. What are some potential applications of BMI technology?

BMI technology has a wide range of potential applications, including assistive devices for individuals with disabilities, brain-controlled prosthetics, and even virtual reality and gaming systems. It also has potential applications in the medical field, such as in the treatment of neurological disorders and brain injuries.

3. What are the current challenges in the field of BMI?

One of the main challenges in BMI research is improving the accuracy and reliability of brain signal detection and interpretation. Another challenge is developing non-invasive methods for obtaining brain signals, as many current BMI systems require invasive procedures. Additionally, there are ethical considerations surrounding the use of BMI technology, particularly in terms of privacy and potential misuse.

4. What skills and knowledge are necessary to work in the field of BMI?

Working in the field of BMI requires a strong background in neuroscience, as well as knowledge of engineering and computer science. Familiarity with signal processing and machine learning techniques is also beneficial. Additionally, strong critical thinking, problem-solving, and communication skills are important for conducting research in this field.

5. How can I get involved in BMI research in grad school?

There are several ways to get involved in BMI research during grad school. You can seek out research opportunities with professors or labs that specialize in BMI, or you can apply for internships or fellowships at companies or organizations working on BMI technology. It is also helpful to take relevant courses in neuroscience, engineering, and computer science to gain a solid foundation in the field.

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