Presentation to UW graduate students in MS&E.

1. What
Should I
Learn
During
My PhD?
Dane Morgan
(University of Wisconsin – Madison, WI USA)
University of Wisconsin - Madison
MSE 900 Virtual Seminar due to COVID-19
April 28, 2020
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2. Some Preliminaries
• Why ask this question?
– I think the answer is not obvious.
– Thinking about it might guide your choices
to yield the best outcome
• Is there one answer to this question?
– No, and it will vary with individual.
– Here I give some possible answers, the are
strongly correlated, and some of might apply
to you to some extent.
• Does Dane know the answer(s) to this
question?
– Not really, but I have some thoughts I will
share.
– I hope you will share your ideas for us here
and future students. 2
What Should I Learn During My PhD?
https://www.masternewmedia.org/what-to-
learn-to-be-successful-p3/

3. Some References
• The Singularity Is Near, Ray Kurzweil; https://www.kurzweilai.net/the-law-
of-accelerating-returns
• The Future Is Faster Than You Think, Peter H. Diamandis
• Grit, Angela Duckworth
• Mindset: The New Psychology of Success, Carol S. Dweck
• https://www.ted.com/talks/steve_jobs_how_to_live_before_you_die
• Randy Pausch, The Last Lecture,
https://www.youtube.com/watch?v=ji5_MqicxSo&vl=en
• https://kk.org/thetechnium/was-moores-law/
• https://cheekyscientist.com/top-10-list-of-alternative-careers-for-phd-
science-graduates/
• https://academicpositions.com/career-advice/the-7-essential-
transferable-skills-all-phds-have
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4. A Short Summary on the Future and
Success
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5. What Will Work Look Like in 10-40 Years?
Technology will change very fast, increasingly
challenging our ability to adapt.
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6. Exponential Change
Technologies increase exponentially (have
doubling time, grow X%/yr), coupled to
accelerated information processing.
This is true for semiconductors (Moore’s Law),
but also true for computation beyond
semiconductors, and for many technologies with
varied levels of coupling to computing. Really
comes from new innovations building on old.
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7. Exponential Change - Computing
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https://en.wikipedia.org/wiki/Accelerating_change

8. Exponential Change - Genetics
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https://www.morningbrew.com/emerging-tech/stories/2020/03/02/beijing-genomics-institute-
offers-100-genome-sequencing

9. Exponential Change - Batteries
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https://kk.org/thetechnium/was-moores-law/

10. Exponential Change – Solar PV
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https://www.vox.com/energy-and-environment/2018/11/20/18104206/solar-panels-cost-cheap-mit-clean-energy-policy

11. Exponential Change – Human
Milestones
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https://singularityhub.com/2016/03/22/technology-feels-like-its-accelerating-because-it-actually-is/

12. What Will Work Look Like in 10-40 Years?
We grow linearly and keeping up will become
increasingly challenging. Next 15 ≈ last 100 years.
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https://steemit.com/ai/@techblogger/tech-news-ai-and-its-exponential-advancement-explained

13. What Will Work Look Like in 10-40 Years?
AI (with robots) will do a lot of we used to do.
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• Computers are now
faster than human
brains.
• Human-like intelligence
is appearing across
many tasks (images,
games, reading,
writing, driving, …)
• Robots enable AI in the
physical world.
Top500.org

14. What Will Work Look Like in 10-40 Years?
AI is better at “closed” than “open”
tasks. It will increasingly supplant
humans in most closed tasks.
Closed tasks: repeat similar
situations with the same goals (e.g.
chess, calculate this property with
DFT).
Open tasks: vary starting points and
goals (e.g., sell this instrument, find
a new superconductor)
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https://link.springer.com/book/10.1007/978-3-030-16800-1

15. What Makes Us Successful?
Achievement = Talent ⨉ Effort2
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Grit, Angela Duckworth
Effort and perseverance (grit) often dominate in success

16. Success: The “Growth” Mindset
• Fixed mindset: Our abilities are fixed (e.g., innate). Creates
need to prove you have these abilities, inhibits exploration.
• Growth mindset: We can change our basic qualities and grow
through effort. Leads to more exploration and success.
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Can “anyone with proper motivation or education …
become Einstein or Beethoven? No”, but “it’s
impossible to foresee what can be accomplished with
years of passion, toil, and training.”
Mindset: The New Psychology of Success, Carol Dweck
Canonical example: Thomas Edison once said of his many
attempts at the light bulb, “I have not failed 10,000 times—I’ve
successfully found 10,000 ways that will not work.”

17. My Prioritized List of What to Learn
During Your PhD
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18. How to learn
1. Learn “how to learn” quickly and effectively.
2. Have growth mindset to learning.
3. Learn when you understand something at the level you
need to, when you need to go deeper, and how to go
deeper (e.g., knowing d(xn)/dx=nx is fine if all you need is
to differentiate some polynomials, not fine if you need to
understand differential equations)
4. Leverage all tools (google, youtube, web of science,
books, people, social media, GitHub, discussion forums,
…) (your old professors may not know how to do this
well).
5. This skill is closely coupled to being able to “solve hard
unstructured problems”. 18

19. To solve hard, unstructured problems
1. Learn to tell a story you believe about your problem
(something to excite your grandparents). If you can’t,
consider changing the problem.
2. Own your problem (don’t give that role to your advisor)
3. Network to get information (don’t be afraid to ask for help
– be a pest)
4. Set SMART goals (Specific, Measurable, Achievable,
Relevant, Time bound)
5. Have a growth mindset (believe you can solve it or
become a person who can solve it)
6. Leverage technology (many older approaches are or
should be disrupted)
7. Do something hard (just doing something hard in your
PhD is invaluable experience)
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20. Your interests, passions, and strengths
1. Following these will support grit, ownership, growth
mindset. If you already know what you want that is great
and you can skip this.
2. Explore books, internships, varied projects, seminars, Ted
talks, thoughtful dinners, … (don’t be afraid to take ~10%
of your PhD to find your passions – talk with your advisor
to engage their support in this as it does not always
directly align with their interests).
3. Don’t be afraid to change projects, advisors, departments,
schools, fields, … (you are younger than you think – losing
2-3 years is worth it if you end up in the right place),
4. Network to get information about different fields, careers,
etc. (e.g., it is amazing who will talk to you if you just try –
be a pest).
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21. Technical knowledge
1. Learn deeply about your discipline.
1. Give this extra time if you are going to be an
academic (~15-20% I think).
2. Do this to learn what deep knowledge means,
even if you will never use the present topic.
2. Learn about the world of science and
technology – it is fascinating and likely the
most important thing in the world.
Understanding it is powerful.
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22. Self awareness
1. Known your strengths and weaknesses (e.g.,
math, presenting, memorizing, …)
2. Learn to play to strengths (e.g., math skills,
computing skills, organizational skills,
mechanistic insight, planning, …)
3. Fix weaknesses you need to fix but don’t fix
everything (e.g. TA to learn to present better,
don’t try to be the perfect presenter if you hate
thinking about it) – growth mindset.
4. Don’t just try to be what everyone else is if it is
not you. Everyone is different.
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23. Professional skills
1. Time management (spend time where is has impact,
how to finish something).
2. Don’t let “perfect be the enemy of the good”.
3. Presenting (pptx, professional talks, brainstorming,
writing).
4. Teamwork (e.g., communicating status).
5. Professional behavior (how to write emails, be on
time, listen, …).
6. Read your audience (when to give 10 second vs. 10
min versions).
7. Highly transferable to any job and easier than most
other things you are trying to learn during your PhD.
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24. 24
http://leadershipquote.org/are-you-strong-intelligent-or-responsive-to-change/
(sadly, it seems likely Darwin never actually said this, but it is still a good point)