I am expected to finish my Ph.D. by the end of the year and I am seriously considering going for a second one. After finishing my master's in Biomedical Engineering, I became interested in Machine Learning and self-taught myself until I eventually landed a Ph.D. project in healthcare. At the risk of sounding cliché, the further I explored the field of ML, the more I felt my competencies were shaky at best. Now, this is not your typical "the more I know, the more I know I don't know" dilemma, since I have never had a formal background in the field.
Sadly, I now realize this Ph.D. was a terrible career choice, as was my choice of Biomedical Engineering for a minor/major.
Biomedical Engineering was a very fun but very challenging major. Fun in the sense that I had exposure to nearly all science fields. Challenging because I had first-contact courses at the level of other Engineering programs that had pre-requisite courses, forcing me to learn an insane amount of material in a semester, only to forget everything afterward since there was no follow-up. Thus, I feel like a true impostor, and sometimes I wonder if I should do another more focused major.
Regarding the Ph.D., I am in a peculiar position since I am pretty much the only one doing ML research in my group and the university does not offer graduate ML courses. Furthermore, since the funding comes from a European project with a specific goal, I have a very narrow set of tasks. I tried to learn everything I could myself, but since I never had a project where I could apply my new knowledge, I ended up needing to learn things over and over.
I would not say I was unsuccessful at all. I have published a technical paper in a top-tier ML conference and a clinical one in a top-tier medical journal (and have two of each kind just about ready to submit before I graduate). However, when I am looking for my next steps, I still feel like I barely know anything and that I will feel like an incompetent forever. I have a good relationship with my supervisor, but he has not published anything in the field for a very long time, so I am pretty much on my own all of the time. I like the freedom I have, but not having someone with field experience to discuss my ideas made me pursue a dead-end path for more than a year. Also, I am now struggling to incorporate the feedback I got when my last technical paper was rejected at a top-tier conference.
Thus, I would like some advice regarding my next move. I am confident I could take a few more practical data science courses to mitigate my blind spots (NLP, I am looking at you) and get hired for a standard Data Scientist job, but ideally, I would like to continue working in a science field. I am therefore wondering whether I should do another, proper Ph.D. since this one was a fraud. I am desperate to feel like I am knowledgeable about something for once in my life and that I am progressing towards a goal I am excited about.
Sorry for the long text. I appreciate your advice.