Switching from phenomenology Masters to machine learning PhD

In summary, you should tell your advisor that you plan to complete your master's project, but you might want to book time for a face-to-face meeting to discuss your future academic aspirations.
  • #1
spaghetti3451
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I am doing a Masters in theoretical physics. It's been half a year since I've begun my Masters.

Recently, I find myself intrigued by machine learning and would like to do a PhD in machine learning after I finish my Masters in theoretical physics.

I am rather afraid to break it to my supervisor that I plan to move into machine learning after my Masters. I am also afraid how he might react if he finds out that I am taking courses in the Computer Science department. I plan to work with machine learning profs to get two recommendation letters, but I guess I must have a third letter from my physics supervisor. I am afraid that he will not write me a good letter for PhD admission into machine learning.

What should I do?
 
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  • #2
So you are withholding information from your advisor that he has a right to know - and is likely to find out - and are afraid this will come out in your letters? ("He wasn't honest with me, but maybe that's OK - he might be honest with you. Can't really tell, can we?") You're right to worry, but I am not sure what we can do about it.
 
  • #3
Okay, I guess I will have to tell my supervisor immediately that my interest has shifted to machine learning.

He might get angry with me for having taken me in as his student, as it's been only six months into the program and my focus has shifted.
 
  • #4
You're not the first student who's interests will have shifted between a master's degree and a PhD. I don't know what the career prospects are in phenomenology, but machine learning is a reasonably hot topic right now with a lot of potential applications in terms of practical projects and it will allow you to develop more marketable skills that will help you through your career. So it's not like this is a completely arbitrary switch.

Most supervisors know that students interests change and will not get upset when they do. They can get upset when the student makes a commitment and then doesn't follow through with it. So tell your supervisor that you intend to complete your master's project. Do the best job you can on it. If you want to add icing on the cake, make sure that he's aware that you're grateful for the opportunity to work on it in the first place, even if in the long term you want to move in a different direction.

The other thing to keep in mind is that supervisors generally don't like being kept in the dark about their students' intentions. If you're taking courses, your supervisor should know about it. He can't properly keep up his side of the student-supervisor agreement if he doesn't.

I realize that having such a conversation can be difficult - particularly if all of your interactions up to this point have been predicated on the fact you intend on continuing on in your current field. Book time for a face-to-face meeting and tell your supervisor that you want to talk about your long term academic aspirations. You never know. It might turn out that he has some kind of connections that can help you out, or at least advice on how to transition into that field.
 
  • #5
Thanks for the advice!
 

Related to Switching from phenomenology Masters to machine learning PhD

1. What is the difference between phenomenology and machine learning?

Phenomenology is a branch of philosophy that focuses on the study of consciousness and human experience, while machine learning is a subfield of computer science that deals with the development of algorithms and models that can learn from data and make predictions.

2. Can I switch from a phenomenology Masters to a machine learning PhD program?

Yes, it is possible to switch from a phenomenology Masters program to a machine learning PhD program. However, you may need to take additional courses or demonstrate proficiency in certain areas to meet the prerequisites for the PhD program.

3. Will my background in phenomenology be beneficial for a machine learning PhD?

Having a background in phenomenology can be beneficial for a machine learning PhD, as it can provide a unique perspective and understanding of human cognition, which can be useful in the development and interpretation of machine learning models.

4. Do I need a strong background in mathematics for a machine learning PhD?

While a strong background in mathematics is helpful for understanding and developing machine learning algorithms, it is not always a requirement for a PhD program. However, you may need to take additional math courses to supplement your background if it is not strong enough.

5. What career opportunities are available with a machine learning PhD?

A PhD in machine learning can lead to a variety of career opportunities, including roles in research and development, data science, artificial intelligence, and more. Many industries, such as healthcare, finance, and technology, are increasingly utilizing machine learning, providing a wide range of potential career paths for those with a PhD in the field.

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