I am currently a masters student that is due to finish early next year. I have a scholarship which covers costs and pays me a modest wage up until and including PhD. I would like to do my PhD but I am concerned about the job opportunities that will be available to me after graduating due to my age and skill set. I would be in my mid 30’s when graduating and would like to work in a non academic, non laboratory environment after graduating. At some time later in life I would like to return to academia but at least after graduating I would prefer to not do so.
How are somewhat older PhD’s perceived by employers outside of academia ? Do they have a harder time being employed ? I have read PhD’s are often considered over qualified or to focused in their knowledge making them not as desirable to employers, is this still the case ?

I need your help on how to write a follow-up letter requesting a professor to act as an academic reference.

I wrote to the professor a couple of weeks ago but so far I have not had any response. The original e-mail explained how we met (I was a visiting student at her lab), how long ago that was, what I´ve been doing since then and why it is important for me to have her recommendation. I know she travels a lot but she always uses an out-of-office auto-reply, which I didn´t get this time, so I don´t know whether she even got the e-mail or not. Should I write a brief note indicating that I sent her an e-mail a few weeks back and then include the content of the original e-mail? (I am writing from another e-mail address in case the first one was blocked by the spam filter). Or should I merge the brief note and the original content in a new e-mail? Any help will be greatly appreciated!

I recently got a tenured faculty position in mathematics. During my PhD and postdoc, I collaborated with the same people on some projects, one big and one small, but most of my time was spent on my own, single-authored projects.

This clearly worked, however I now feel like I am missing out. I see all these people at conferences interacting, breaking ground on new knowledge together and having rewarding time working with other people. How do I get to that point?

Not to fall into stereotypes, but I am unfortunately a bit socially awkward, which does not help. I can go out and have fun with other young mathematicians, but walking up to someone and starting talking about a topic of collaboration seems to be out my reach. It never goes further than “I have a question”, listening to the answer, and going back to talk with my friend-colleagues.

I am a civil engineering graduate (graduated 2018) trying to break into the analytics field. I graduated from a tier 2 college in my country with an average GPA of 3.0/4.0 (7.5/10.0). I am looking for masters in applied statistics since I have always been interested in mathematics but didn’t have the opportunity to take it up.

I am taking a year off to improve my skill set as well as re-evaluate my options and I realize that I am not interested in Civil engineering and I don’t find it easy to break into this field either without contacts. I have done a project in construction management with AI, optimization techniques, etc. I am good with coding and trying to get certifications for that. But I want to know what skills can make me a strong applicant for a masters in applied statistics with my profile. what should I do?

I am really confused and I will really appreciate any direction I can get.

My friend is soon to obtain her doctoral degree in applied physics and start postdoc. She is provided by the department a chance to choose what to be displayed on her degree (between D.Eng. and Ph.D., but both in applied physics). She is actually doing purely theoretical condensed matter physics although her department is named applied physics. She says that she will try to stay in the same academia, but not excluding the possibility of moving out if not going well.

She asked me and it’s not quite clear to us what the difference might be and what might be affected in the future.

First question: I have an important article on arXiv and I updated its title in the 2nd version. But after that Google never updated the article title and I know people are citing my 2nd version and because of this issue with Google citations are not visible. How can I force Google scholar to refresh my article list and update any possible change/citation?

Second question: I cited a previous work of mine in an article that is already published and Google detected it but Google didn’t catch the citation. How can I make Google scholar to catch the citation?

Recently I submitted an IEEE conference paper about an open-source machine learning project/framework related to mobile networks. Now, I also want to demonstrate its features at another IEEE conference using a 2-page demo paper.

Considering the original paper is still in reviewing process, is it ethical to submit a related demonstration paper with the same approach to another conference. I mean from self-plagiarism aspects, can I use the same title and experiment results in demo paper as well just for showcasing purposes? If not, how can I also reference the original paper considering it is not published/accepted yet!

I am writing a manuscript dedicated to the classification of natural processes occurring worldwide. In this study, I create a composite model involving a classifier, i.e. a Neural Network model, that will be used to process the classification. The study discusses which variables, related to the observed natural processes, are more important for the classification procedure (e.g., weight matrices are described and discussed).

To explain the method, I briefly give an overview of machine learning (principles) in 3 sentences and relate it to my study. In addition, I also explain what are neural networks, and the explanation is made in the appendix (3 pages). For both, machine learning and neural network, I use a citation pointing directly to a book.

Is it preferable to leave a citation inside my manuscript so that the reviewer just takes a look at the cited book to understand how neural networks work, or can I explain the concept in the appendix (but in this case I use different citations for detailing the explanations)?