Hide table of contents

I am looking to interview individuals who have exited their PhDs (at any given time) and are continuing to work towards an impactful career.

If you are someone who has quit their PhDs and would like to help others who may be considering a similar career path, please register your interest in being interviewed here.

Background

I have recently started a one-year break from PhD (August 1st) and have received EAIF funding to help me transition towards an impactful career. My PhD was focused on improving biosafety and biosecurity regulation in the global south, and I have decided to take a year off to consider several factors related to the decision of leaving it. While doing my PhD, I also was a coach at Effective Thesis helping people with thesis topics and career choices. I hope to leverage these two experiences together in writing up advice for those thinking about exiting PhDs.

In the process of quitting my PhD, I discovered that there are very few resources that actually help one think through this decision and that helps you continue working towards an impactful career path. When writing this post last year as a joke with several others, I received many messages asking me to write up advice on how to dropout effectively.

As such, I will later post advice on “How to quit your PhD effectively”. Rather than using my own experience as the only source of advice, I want to interview several (approximately 10) people who have left their PhDs and either switched to more impactful career paths or remained on an impactful career trajectory.

My goal is to better understand the challenges that people face when making the decision to leave a PhD program, as well as the strategies and resources that can help individuals successfully transition into new careers.

What will the interviews look like?

I intend to have an online video call with all those who are interested for approximately 1.5 hours. These will be semi-structured interviews. Essentially, I will focus on three key phases of exiting your PhD. First, the decision-making process and how you ended up at that decision. Second, the technical processes of leaving your PhD and how you navigated that experience (e.g. dealing with supervisors, institutions or visa problems). Finally, I will ask you about your transition and what resources and strategies were useful in ensuring a really smooth transition towards your current career path (e.g. rest first, apply for jobs later or focus largely on your resume building or connections).

I will also be attending EAGxAustralia and EAGxPhilippines in case anyone wants to meet in person at those conferences.

Timeline

I hope to conduct all my interviews by mid-November and will leave this form open till mid-September (approximately 15th September 2023). Please feel free to share it with anyone who you know will be interested in sharing their experience.

Please feel free to email me at vorathep112@gmail.com or comment below with any questions. Again, please register your interest here.

This is my first post on the forum, so apologies if there are any errors! Please feel free to point them out and I will edit them!

Comments4


Sorted by Click to highlight new comments since:

Registered. It also seems valuable to talk to impact-driven people who seriously considered quitting but then decided to finish their PhD as (a) it is not obvious to me that quitting is always the right choice and (b) it might be useful to know common reasons why people decided to continue working on their PhD. 

Thanks Jona! I did think of this too, but chose to not recruit those in this round for 3 reasons:

  1. There are more resources out there for continuing to finish a PhD (marginally).
  2. I did not want to create confusion in the recruitment process and may do a separate post later to interview for those after!
  3. Typically in the decision matrix of choosing to stay or leave a PhD, the staying side usually has a lot more supporters (supervisors with various reasons, your original thought of impact and decision, talking to Effective Thesis to see how you can make your thesis more impactful).

However, I do see your point that any piece of advice should not skew too much on one side of the decision that it makes it not great advice. If I feel like the advice I write out is that way, I shall definitely interview more people as you suggested!

This is a cool project! I've registered my interest.

Registered. I'll also be at EAGxAustralia and would love to chat about this with you :)

Curated and popular this week
 ·  · 12m read
 · 
Economic growth is a unique field, because it is relevant to both the global development side of EA and the AI side of EA. Global development policy can be informed by models that offer helpful diagnostics into the drivers of growth, while growth models can also inform us about how AI progress will affect society. My friend asked me to create a growth theory reading list for an average EA who is interested in applying growth theory to EA concerns. This is my list. (It's shorter and more balanced between AI/GHD than this list) I hope it helps anyone who wants to dig into growth questions themselves. These papers require a fair amount of mathematical maturity. If you don't feel confident about your math, I encourage you to start with Jones 2016 to get a really strong grounding in the facts of growth, with some explanations in words for how growth economists think about fitting them into theories. Basics of growth These two papers cover the foundations of growth theory. They aren't strictly essential for understanding the other papers, but they're helpful and likely where you should start if you have no background in growth. Jones 2016 Sociologically, growth theory is all about finding facts that beg to be explained. For half a century, growth theory was almost singularly oriented around explaining the "Kaldor facts" of growth. These facts organize what theories are entertained, even though they cannot actually validate a theory – after all, a totally incorrect theory could arrive at the right answer by chance. In this way, growth theorists are engaged in detective work; they try to piece together the stories that make sense given the facts, making leaps when they have to. This places the facts of growth squarely in the center of theorizing, and Jones 2016 is the most comprehensive treatment of those facts, with accessible descriptions of how growth models try to represent those facts. You will notice that I recommend more than a few papers by Chad Jones in this
LintzA
 ·  · 15m read
 · 
Introduction Several developments over the past few months should cause you to re-evaluate what you are doing. These include: 1. Updates toward short timelines 2. The Trump presidency 3. The o1 (inference-time compute scaling) paradigm 4. Deepseek 5. Stargate/AI datacenter spending 6. Increased internal deployment 7. Absence of AI x-risk/safety considerations in mainstream AI discourse Taken together, these are enough to render many existing AI governance strategies obsolete (and probably some technical safety strategies too). There's a good chance we're entering crunch time and that should absolutely affect your theory of change and what you plan to work on. In this piece I try to give a quick summary of these developments and think through the broader implications these have for AI safety. At the end of the piece I give some quick initial thoughts on how these developments affect what safety-concerned folks should be prioritizing. These are early days and I expect many of my takes will shift, look forward to discussing in the comments!  Implications of recent developments Updates toward short timelines There’s general agreement that timelines are likely to be far shorter than most expected. Both Sam Altman and Dario Amodei have recently said they expect AGI within the next 3 years. Anecdotally, nearly everyone I know or have heard of who was expecting longer timelines has updated significantly toward short timelines (<5 years). E.g. Ajeya’s median estimate is that 99% of fully-remote jobs will be automatable in roughly 6-8 years, 5+ years earlier than her 2023 estimate. On a quick look, prediction markets seem to have shifted to short timelines (e.g. Metaculus[1] & Manifold appear to have roughly 2030 median timelines to AGI, though haven’t moved dramatically in recent months). We’ve consistently seen performance on benchmarks far exceed what most predicted. Most recently, Epoch was surprised to see OpenAI’s o3 model achieve 25% on its Frontier Math
Omnizoid
 ·  · 5m read
 · 
Edit 1/29: Funding is back, baby!  Crossposted from my blog.   (This could end up being the most important thing I’ve ever written. Please like and restack it—if you have a big blog, please write about it). A mother holds her sick baby to her chest. She knows he doesn’t have long to live. She hears him coughing—those body-wracking coughs—that expel mucus and phlegm, leaving him desperately gasping for air. He is just a few months old. And yet that’s how old he will be when he dies. The aforementioned scene is likely to become increasingly common in the coming years. Fortunately, there is still hope. Trump recently signed an executive order shutting off almost all foreign aid. Most terrifyingly, this included shutting off the PEPFAR program—the single most successful foreign aid program in my lifetime. PEPFAR provides treatment and prevention of HIV and AIDS—it has saved about 25 million people since its implementation in 2001, despite only taking less than 0.1% of the federal budget. Every single day that it is operative, PEPFAR supports: > * More than 222,000 people on treatment in the program collecting ARVs to stay healthy; > * More than 224,000 HIV tests, newly diagnosing 4,374 people with HIV – 10% of whom are pregnant women attending antenatal clinic visits; > * Services for 17,695 orphans and vulnerable children impacted by HIV; > * 7,163 cervical cancer screenings, newly diagnosing 363 women with cervical cancer or pre-cancerous lesions, and treating 324 women with positive cervical cancer results; > * Care and support for 3,618 women experiencing gender-based violence, including 779 women who experienced sexual violence. The most important thing PEPFAR does is provide life-saving anti-retroviral treatments to millions of victims of HIV. More than 20 million people living with HIV globally depend on daily anti-retrovirals, including over half a million children. These children, facing a deadly illness in desperately poor countries, are now going
Recent opportunities in Building effective altruism
27
CEEALAR
· · 1m read
34
cescorza
· · 2m read