I am an international student who is going to complete a PhD in physics in Australia in about six months (specifically, I worked on quantum communication protocols). Before my PhD, I studied Electronics and Communication Engineering in my undergrad. I am considering to shift to industry, possibly in Hong Kong, Singapore or Australia for the next 4-5 years and eventually get settled in India. I am looking for jobs that involve a fair bit of mathematics. With that in mind, a little bit of research introduced me to quantitative finance. I am writing down some aspects about myself as objectively as possible.

**Particular mathematics that I have used in my research:**

Linear algebra, probability, information theory, signal processing.

**Exposure to coding:**

**Matlab:**I have a good exposure to Matlab, for example, I have a paper where I modelled atmospheric turbulence. I have also created several optical signal processing in Matlab. I have used a convex optimisation package, like CVX.**Python:**Although I am not as fluent in it as in Matlab. Mainly it boils down to do a quick google search for the exact Matlab equivalent command that I am looking for, and after that I can fairly easily implement the algorithms. Also I have a good of exposure to the libraries like sci-kit learn.**C:**In my undergrad, I have done basic programming algorithms like sorting, printing patterns, data structure. However, I have not prepared particularly for any coding interview.

**Exposure to machine learning and deep learning:**

- I have done a deep learning workshop from Spaceport AI that involved 3 Kaggle projects. There were projects like twitter sentiment analysis or recognising cats and dogs.
- Currently, I am working on a physics project that involves machine learning, the work should appear on the arXiv soon.
- I am currently doing a Udemy certification course.
- However, I haven't taken a machine learning as a core course, I know a bit of linear algebraic model behind neural network or the principle behind gradient descent algorithms but if someone asks me to solve an exercise problem from Christopher Bishop, I will get stumbled for a while. The point is, if it is worth investing time to get well versed in the underlying math I can do that.

**Soft skills:**

I am an introverted person, however, my Ph.D. gave me several opportunities to improve my communication and presentation skills. Based on my personality, I would like to be the guy who works on mathematical and statistical modelling and decode the state of the art trading papers.

**Weaknesses I can think of:**

- I don't have a finance background.
- I haven't worked on SQL, however unlike data science jobs, I have seen that most quant ads don't have this requirements.
- I need to prepare myself with coding interview questions.

__Questions:__1) How much chance do I have if I want to land a quant job immediately?

2) Assuming the chances are low for 1), what do I need to work on if I want to land a job before, say June 2021? Realistically, I will be busy in writing a few papers and after that I will write my thesis. So I can dedicate 2-3 months for job preparation.

3) If I do a post doc, in a field say quantum machine learning, then how will it affect my job prospect? (There are articles about doing finance using quantum computers, but I am not sure how much my degree will boost my credibility.)

4) How secure and stable is the job market, now given the COVID situation?

5) Given this pandemic situation, I don't have much opportunity to do networking. Can you guys suggest strategies or opportunities to do networking?

Any advice would be highly appreciated!