The emergence of Elon Musk’s Neuralink in 2017 sparked a burst of research and development in the world of neurotechnology, with the market growing from $8.4B in 2018 to $13.3B in 2022 (Neurotech Reports). This boom in the neurotech market will no doubtedly inspire young engineers and scientists who want to join the battle at this scientific frontier.
However, the interdisciplinary nature of neurotech, combined with the relative youth of the neurotech field makes it difficult to know how best to prepare for a career in this field. This article looks at the educational backgrounds of employees at ten neurotech companies to get a sense of which educational paths are most commonly seen in individuals who work in the neurotech field.
To accumulate data on educational backgrounds of employees, we used LinkedIn’s “People” tab which shows a split of location, school, role, education, and skills.
Caption: The LinkedIn People page displays “What they studied” in this format. These numbers are based on the employee’s self-reported LinkedIn profiles.
For this report, ten companies were chosen; a mix of invasive and non-invasive neurotech companies; all having more than 20 employees on LinkedIn.
We categorized “What they studied”, with similar disciplines grouped together such as Computer Science and Computer Engineering. These 9 categories of educational backgrounds were most common among the ten companies’ employees.
- Computer Science (Computer Engineering, etc.)
- Electrical Engineering
- Bioengineering (Biomedical engineering, etc.)
- Neuroscience, Biology
- Mechanical Engineering (Robotics, etc.)
- Business (Economics, Communications, Entrepreneurship, etc.)
Caption: Table of each company’s employees categorized by educational background. Data acquired from LinkedIn of Kernel, OpenBCI, Neuralink, Synchron, Neurable, Paradromics, NeuroSky, EMOTIV, BlackRock, Cognixion.
Something to note is that these educational backgrounds are self-reported, and also may be incomplete as not all employees have an active and up-to-date LinkedIn profile. The data also does not reveal the level of degree (Bachelors, Masters, etc.).
Initial thoughts, which backgrounds are the most common?
Upon initial inspection of the data, it is clear that these companies are mostly comprised of employees who are scientists and engineers with Computer Science topping all other educational backgrounds, and Electrical Engineering and Bioengineering following it.
Caption: Split of neurotech employees by educational background. Data acquired from LinkedIn.
Though we see quite the number of engineers, the number of employees with backgrounds in Physics and Mathematics is interesting as well. These disciplines are not in direct relation to neurotech, but they serve as the foundation of many of the other disciplines including neuroscience and engineering.
Another noteworthy observation is the surprisingly low number of neuroscience and biology backgrounds. The word neurotech is half comprised of “neuro”, but when creating devices to interface with the brain, the hard skills that are acquired in engineering disciplines may be valued more by these companies.
Non-invasive vs Invasive: Meeting the Technology’s Needs
Caption: Split of neurotech employees by educational background, non-invasive vs invasive technology. Non-invasive companies (Kernel, OpenBCI, Neurable, NeuroSky, EMOTIV, Cognixion) had 239 employees in total. Invasive companies (Neuralink, Synchron, Paradromics, BlackRock) had 321 employees in total. Data acquired from LinkedIn.
Scrutinizing the difference between companies building non-invasive and invasive technologies, there is a clear contrast in the skillsets that are valued between the two types of neurotech. Although Computer Science was the dominant background among all ten companies, the non-invasive companies employ a significantly higher percentage of them compared to the invasive neurotech companies.
All six non-invasive companies have a fifth or more of their employees with Computer Science backgrounds, while the four invasive companies peak at 18% at Neuralink, with Paradromics having only 4% of its employees with a Computer Science background.
Caption: Proportion of computer science backgrounds, blue bars are non-invasive companies and orange bars are invasive companies.
As a hypothesis, the invasive neurotech companies may not require extensive emphasis on software interfaces compared to research, testing, and physical development of BCIs, especially accounting for the fact that most of these companies are building clinical BCIs (at least initially).
In terms of invasive technologies, these companies have a higher proportion of bioengineering, neuroscience and biology, and mechanical engineering backgrounds. This may speak to the nature of invasive technologies requiring more scientific knowledge of the brain like neuroanatomy and neurobiology, and a different set of engineering skills (biomedical and mechanical) that may not be as relevant for less regulated non-invasive products.
Another important point here is that the proportion of employees with electrical engineering is comparable between the two types of companies. This might be revealing the necessity of electrical engineers for any type of hardware interface for the brain.
A Deeper Dive: Each Company is Different
When looking closer at the split of backgrounds at each company, interesting patterns appear, revealing somewhat of the company culture.
“Training the market” was a huge strategy discussed by Stanley Yang of NeuroSky in a previous NeurotechJP article. As pioneers of the consumer BCI company, NeuroSky focused on educating consumers about neurotech and its capabilities, leading to the establishment of the consumer BCI market. This was driven by marketing and clever strategies to increase the understanding of neurotech by the public, with one of NeuroSky’s products appealing to a familiar concept from Star Wars: the Force.
With NeuroSky’s early focus to train the market, it is clear why the company has 8 employees with business backgrounds, the highest proportion of all ten companies by far.
Synchron is also an intriguing case in which the most common background is in bioengineering. Stentrode, Synchron’s core technology which won the BCI Award 2021, travels through the blood vessels to record and stimulate the brain. This approach is very unique compared to traditional invasive techniques that implant electrodes directly in the brain tissue and could be a reason why the skills acquired during a biomedical engineering education are important for Synchron.
So, what is the best educational background for Neurotech?
The simple answer is to get an engineering education. From a pure numbers standpoint, engineering backgrounds account for more than half of all employee backgrounds from our survey. Though not a causatory relationship, neurotech companies will always need engineers to build both hardware and software interfaces.
Important to grasp is that education, especially the degree is rarely the dictator of skillsets, and other experiences such as independent projects, research, and internships can help develop skills outside of coursework.
With neurotech’s interdisciplinary complexity, no single employee will have the education and experience to have the expertise to work on every aspect of the neurotech stack.
Looking at the Neuralink Software Engineering job listing, there is an emphasis on being a “cross-discipline team member.”
You are a cross-disciplinary team member. You are excited to work with and learn from software, mechanical, electrical, materials, biological engineers, and neuroscientists. You are comfortable communicating across teams.
The process is truly a team effort, only achievable with a multitude of perspectives coming together at the intersection of neuroscience and technology.
Another key observation about Neuralink’s listings is the footnote underneath the departments:
No prior experience in neuroscience is necessary — we will teach you everything you need to know.
The team would rather hire the best engineers regardless of neuroscience experience, and teach them the necessary science for their application.
This perspective teaches us that neurotech is simply an application of engineering for interfacing with the brain. Sensors, data analysis software, and user interfaces are ubiquitous across technology companies, and neurotech may not be so dissimilar when reduced to its basic components.
Finding your path: what to consider?
For readers who are interested in working on neurotech but have yet to choose a discipline or major, there are two questions that may help guide your educational path.
Ask yourself what applications of neurotech you are personally interested in, and what part of the neurotech stack you’d like to work on.
If non-invasive BCIs for measuring focus and productivity is most interesting, a Computer Science degree may serve higher utility than a Neuroscience degree. On the contrary, if developing BCIs for restoring movement and speech brings more fulfillment, a Bioengineering or Neuroscience education may align better with invasive neurotech companies’ needs.
Neurotech is multidisciplinary effort, requiring ASICs (application specific integrated circuit), sensors, data analysis, machine learning, user interface, research, marketing, sales, and so on. Even within a single company, employees are likely working on very particular aspects of the product. Considering whether you want to conduct clinical trials, develop hardware, or write code is a basic but crucial thing to keep in mind.
In this article, we looked at the educational backgrounds of employees working at ten neurotech companies to understand current trends and patterns.
The team at NeurotechJP is also comprised of many different disciplines, with educations in Neuroscience, Computer Science, Engineering, Communications, and Business.
*Educational backgrounds have been categorized very leniently for the sake of simplicity. Neuroscience and biology are grouped together but in reality, a neuroscience education is much more in-depth in neurobiology, neuroanatomy, and electrophysiology whereas a biology education could entail more coursework in areas like genetics and molecular biology. LinkedIn numbers reflect any education level (Bachelors, Masters, Ph.D., etc.) and likely varies largely between each individual’s educational experience. Even within a single discipline like Electrical Engineering, there are concentrations of courses that can vary from Embedded Systems to Sustainable Power Systems.