Navigating Quantum Computation: My Masters and PhD Prospects

[jamesb1]

I'm currently in my final year of BSc(Hons) in mathematics and computer science & A.I (applied math stream). Indeed, I'm starting to think about what masters I want to pursue and the kind of subject I would like to specialize in. I am really interested in quantum computation and the prospects of quantum artificial intelligence, but I am unsure how I can go about this. The imperial college London would be my top choice if I had to undertake a masters in artificial intelligence but it has only one unit called quantum computation in its syllabus so it may not be sufficient background for me to build or pursue a further career in this field, especially if I want to continue to a phd. Then again I am not sure, maybe I'll be allowed to consider quantum computation for my dissertation and it will not matter anyway. I was also considering taking a masters in theoretical physics (if I am allowed of course) and this will give me a good foundation for quantum computation, but this scares me since it seems like a massive jump from mathematics and computer science. In the end I really want to conduct research on quantum computation and artificial intelligence so this is a very confusing situation for me. Any insight that can be shared on this matter? Which choice should I consider more for this path?

 

[heatengine516]

I only know how college works in the U.S. Sounds like you are in Europe. So I don't know how much research you do in a masters program in Europe.

The two major things in this case are algorithms and obviously quantum mechanics. I know that Seth Lloyd does research in quantum artificial intelligence, and he has a PhD in theoretical physics. There are of course people who have contributed to quantum computing research that are not physicists(Shor for example). I think the obvious route would be to do a masters in either field (CS or physics) at a university where your thesis research could be in quantum machine learning or any subtopic in theoretical quantum computation (error correction, etc.). It's an interdisciplinary field so you may even find universities that have quantum computing groups in the CS department. It's not so much the title of the degree that counts, but what topic you do your research in.

 

[jamesb1]

I only know how college works in the U.S. Sounds like you are in Europe. So I don't know how much research you do in a masters program in Europe.

The two major things in this case are algorithms and obviously quantum mechanics. I know that Seth Lloyd does research in quantum artificial intelligence, and he has a PhD in theoretical physics. There are of course people who have contributed to quantum computing research that are not physicists(Shor for example). I think the obvious route would be to do a masters in either field (CS or physics) at a university where your thesis research could be in quantum machine learning or any subtopic in theoretical quantum computation (error correction, etc.). It's an interdisciplinary field so you may even find universities that have quantum computing groups in the CS department. It's not so much the title of the degree that counts, but what topic you do your research in.

You're very right, thank you :)

 

[f95toli]

Quantum Computing is a VERY young field and I wouldn't advice anyone to actively pursue it as a specialization. The "hardware" can be implemented in lost of different ways, and each method requires a different specialization/background (say atomic physics of superconductivity) meaning the actual work will also be very different. Hence, quantum computing is a sub-field in many different research areas.
There is tiny number of people who do "hardware independent" theoretical work and their background seems to be either physics or maths (I don't believe I've ever met someone who had a background in CS). Moreover, most of them also do other work in related areas. The main problem is that the hardware is way behind the theory, meaning it is currently impossible to implement any of the algorithms that have been developed expect in some very simplified (and not useful) cases so few people are interested in developing algorithms (with some notable exceptions that might influence how the hardware is implemented, e.g surface codes).