In this video, I dive deep into a topic that is often overlooked but critical for any PhD student: managing risks during your PhD.

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When we think about doing a PhD, we often focus on the research, experiments, and writing, but there's another layer that no one really prepares you for—risk management. Throughout your PhD, you’ll encounter countless decisions that either push your research forward or create potential setbacks. Some of these choices may seem harmless at first but can have major consequences down the line if not handled carefully.

As a PhD student, it’s easy to get caught up in chasing the big, bold, high-impact results—what I refer to as “risky PhDs.” While aiming for breakthroughs is important, too much risk can lead to dead-ends, anxiety, and even delays in finishing your degree. On the other hand, playing it too safe might not yield the kind of results that can make your research stand out. That’s why finding the right balance is key.

In this video, I’ve developed a simple framework to help you evaluate and manage risks at different stages of your PhD. This framework can help you organize your ideas, assess their potential impact, and identify any risks—such as access to resources, data, or funding—that may stand in your way. I’ll explain how you can categorize your research projects into different levels of risk, and how to mix high-risk, high-reward projects with lower-risk ones. This balance will help you keep momentum in your research while avoiding unnecessary stress or setbacks.

By the time you finish watching, you’ll have a clearer understanding of how to approach your PhD strategically, with a focus on managing risks during your PhD. Whether you’re just starting out or in the later years of your degree, learning to manage risk is essential to making sure you not only finish but finish with strong, impactful research. Let me know your thoughts in the comments, especially if you’ve encountered risks in your own PhD journey.

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▼ ▽ TIMESTAMPS
00:00 Intro
01:16 Perfecting Progress
02:58 Identifying Risk/Cost
03:31 Traffic Light System
05:35 Data Risk
06:08 Experimental Risk
07:01 Financial Risk
07:31 Ethical Risk
08:01 Framework Computation
08:54 Traffic Light System
10:00 Experimental Table
13:08 Management Framework Overview
13:58 Outro

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