“Selecting a Thesis Topic” Old Advice New Science
Abbas Ourmazd
[email protected]
Acknowledgments Collaborators:
Russell Fung Dilano Saldin Valentin Shneerson
Discussions:
Daniel Agterberg Paul Lyman Valerica Raicu Marius Schmidt Dmitri Starodub Mike Weinert
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Important Note
Can recommend all members of Physics faculty Dedicated experts, nice and caring people
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Outline What I wish I had heard How to pick a thesis topic
What field am I in? Why?
Who am I? Background and interests
What are the technical challenges? What would you be working on?
Conclusions Abbas Ourmazd
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I wish I Had Heard!
Don’t be an Idiot!
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Picking a Thesis Topic Pick your field Growing, but not too big Committed funding sources Intellectual excitement
Pick your advisor Strong track record Lots of contacts
Work your butt off If you don’t know what it means, leave physics now!
Get lucky “The harder I work, the luckier I get”
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Who is Abbas Ourmazd? Oxford, Göttingen, Bell Labs Worked with 4 Nobel laureates Arno Penzias, Steve Chu, Horst Stoermer, Tony Leggett Befriend me; you might win too!
Leadership in academia, industry, national labs, startups
Vice Chancellor for Research Head, Microphysics Research, Wireless Strategy, AT&T Director of national lab in Germany Launched, managed & sold two startups
Fellow of American Physical Society, AvH Fellow, etc >130 papers, 10 patents, prizes
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My Field Structure of single biological molecules & nanoparticles Intersection of physics, biology, and informatics
Important for fundamental science & application “To understand function, study structure” Crucial to health & pharmaceutical industries
Biomolecule structure largest use of modern X-ray sources From academia & industry Focus of significant VC/start-up investment
Rapidly growing, BUT hitting key bottleneck One person’s bottleneck is another’s opportunity Multi-billion dollar investments committed worldwide
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Protein Structures vs Year
No. of Structures Deposited
New Structures Deposited in PDB Each Year 6000 EM plotted but not visible Additions/yr: ~20
NMR
5000 4000 3000
X-rays
X-ray
2000 1000
19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 02 20 04 20 06
0
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Why Single Molecules? The Scorecard
Number
Proteins sequenced
Percent
>750,000
Protein structures determined
44,700
