How I turned seemingly 'failed' experiments into a successful PhD
Turning “failed” experiments into a successful PhD is portrayed less as a rare talent and more as the default reality of modern research, where most projects don’t work as planned and null results are hard to publish. Commenters contrast different PhD structures in Europe and the US, emphasize the roles of perseverance, luck, funding politics, and collaboration, and note how systemic pressures to publish can overshadow the core goal of deepening understanding. Several share that managing multiple backup projects, reading extensively, and asking for help early are practical ways to survive and grow as a researcher in this environment.
Nature of “failed experiments” in PhDs
- Some say the described experience is entirely typical: everyone must turn dead-ends into something thesis-worthy before funding runs out.
- Others argue the piece doesn’t claim uniqueness; it’s just a personal narrative about feeling like a failure.
- Debate over whether the highlighted protocol change that eventually worked really counts as “failed experiments” or just normal troubleshooting.
- Several note that genuine null results usually do not become theses or publications, making this case somewhat unusual.
Perseverance, luck, and academic politics
- PhDs are seen as largely about perseverance, but commenters stress luck (advisor changes, pandemics, visa issues) and strategy (field choice, funding density, politics).
- Oncology is described as far better funded than infectious disease due to market size and government priorities; trend-chasing (e.g., CRISPR, CAR‑T, mRNA, AI) strongly shapes careers.
- NIH RePORTER is cited as an underused tool to see where money actually goes.
Handling null/negative results and the nature of science
- Negative results are hard to publish and rarely form theses; students often must “twist” them into a different, publishable question.
- Some celebrate initiatives and journals that explicitly publish negative results, arguing they prevent wasted effort and can spark new ideas (even in math).
- One theme: science advances mainly by disproving hypotheses, not by “proving” them.
Structure and timelines of PhD programs
- Major differences noted between US and various European systems:
- In parts of Europe, funding is often ~3 years with little coursework; failing to finish can mean losing building access.
- UK and Australia typically fund ~3.5–4 years; US programs can stretch 5–7+ years with more coursework/teaching.
- Requirements vary widely: some programs formally demand multiple first‑author publications; others require only one or none explicitly.
PhD simulator and lived experience
- Many discuss a browser “PhD simulator”: some find it uncannily accurate, others think it exaggerates.
- Shared experiences include long durations, ideas failing for years, and rewriting work “as if it was great.”
- There’s substantial reflection on whether doing a PhD is economically and personally worthwhile; some regret it, others describe it as an ideal, intellectually free period.
Practical research advice and collaboration
- Strong emphasis on:
- Asking for help early; many realize too late that a short discussion can unblock months of stuck work.
- Collaboration and idea exchange as central to research success.
- Starting with extensive reading to avoid reinventing the wheel, though some in CS favor rapid prototyping instead.
- Maintaining multiple and backup projects, expecting most experiments to fail or never be published.
- Divergent views on the “true” goal of a PhD: personal understanding vs. hitting publication quotas; tension between intrinsic learning and publish‑or‑perish incentives is repeatedly highlighted.