Application of Machine learning in modelling experimental system as a PhD topic

I am working as a control Engineer in a high energy physics lab. I am looking for a PhD thesis topic. Our experimental system is highly non linear and can't be modeled using standard white box approach. I am thinking of developing Neural Net models of the sensors attached to the experimental system. Also in this way I can model the system with primary inputs and outputs.

So the basic idea is to have a data driven system identification and data driven sensor model.

I wanted your feedback if this can be potential thesis problem. Thanks.

Topic neural machine-learning-model dataset

Category Data Science

1
answered at

It's very unlikely that anybody here has the expertise needed to assess the validity of a PhD topic, especially about a highly specialized (and unspecified) experimental system. You should discuss this with your potential academic supervisor, and I'd suggest you try to find a co-supervisor or collaborator expert in DL as well.

In general for a decent PhD topic you would need to make sure that it hasn't been done before and that there are reasonable grounds to think it's feasible. Study the state of the art and find out if anything similar has been published:

  1. If something very close already exists, it might be too trivial
  2. If there's nothing even remotely close to it, it's probably not feasible or very hard.

Good luck!

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