Reader Question: What Is the Most Difficult Specialty Within Electrical Engineering?

October 21, 2019 by Kate Smith

There are some disciplines that many call "black magic"—but which is the most difficult field an EE can pursue?

Electrical engineering is a truly diverse field. Two professional EEs who come from the same educational background can land in extraordinarily different jobs, perhaps test and measurement for high-density memory or perhaps designing algorithms for military applications.

The US Bureau of Labor Statistics estimated that there were 330,300 electrical engineering jobs in the USA in 2018. Amongst these 300K+ engineers, there are many specialties. 

But... which is the most difficult field?


Image used courtesy of Miguel Á. Padriñán


Here are five disciplines within electrical engineering that may be contenders.


RF (Radio Frequency)

The term "RF" and the term "black magic" seem to go hand-in-hand in industry.



In a world where connectivity is expected for many devices, RF is a lynchpin technology. It can be mildly unsettling, then, to realize how many EEs find the discipline of RF design entirely opaque. 

One of the most common trends you can see in action in industry today is the growth of RF modules. By packaging complex RF circuitry into modules, circuit designers can reap the benefits of connectivity without needing to learn its intricacies. 

For those looking for a way to get a handle on the basics, check out Robert Keim's free textbook on RF analysis and design.


Neural Network Design

Neural networks seem omnipresent (if research news is anything to go by). ANNs (artificial neural networks) are systems meant to mimic the functionality of a human brain in terms of data processing. Their applications are expansive, proving useful in interpreting data across fields like astronomy, biology, and meteorology.

While very basic ANNs can theoretically be put together using Python, the challenge of developing high-level ANNs arguably lies in training the network appropriately. Future deep learning algorithms may come up against the limits of our understanding of neurology as much as they will be useful in surpassing them.


EMC Design

EMC (electromagnetic compatibility) design involves considering two sides of the same coin: reducing a product's vulnerability to EMI (electromagnetic interference) and assuring that the product does not emit EMI that could threaten other devices.

The process of EMC design involves the reduction of interference and shielding against EMI. These are accomplished using methods implemented across the development process, from initial designs to PCB design to cable design to enclosure design and beyond to the use of I/O filters. Additional consideration must also be given to meeting stringent regulations regarding EMI for reliability and tolerances.


Machine Vision

How do you teach a machine to see? Machine vision is defined as the creation of technology and methods that allow image-based analysis of environmental data. 

Machine vision is crucial in the developing IIoT (industrial internet of things) space. Smart factories are now taking advantage of machine vision for error identification/quality assurance, product tracking, and guidance for robotic systems. More sensational applications of machine vision include autonomous vehicles, where algorithmic data processing can help a car's sensor systems identify objects.


Many familiar companies provide solutions for the use of machine vision in factory automation. Image from ams


What's even more impressive is that machine vision can combine via sensor fusion with other sensor data to create some of the most extensive environment sensing systems known to man. 


Space Systems Development

The radiation, cold, size and power constraints, and ruggedization involved in designing electronics destined for the stars make this specialty truly demanding. That being said, of all the harsh environments in all of the universe, perhaps the vacuum of space isn't the least friendly to electronics.

Increasingly, designing space systems means more than making circuits that can withstand even prolonged deep space travel—designers are developing probes and rovers that are meant to function in some of the harshest environments we've ever come across, including raging storms and skimming the surface of stars.

If you'd like proof that aerospace system designs can stand the test of time, read AAC's articles on the engineering marvels of the Voyager spacecraft in our series designed by Mark Hughes.



These are our nominees for the most difficult EE fields. Now we want to hear from you. 

What is the most difficult discipline in electrical engineering?

Whether one of these specialties is your own or you're simply marveling at your peers' handiwork, share your perspective in the comments below.