In this talk, Dr. Micah Webster will discuss his journey from UCI to the NSA (with a 12-year stop in academia) by focusing on learned insights that can propel your career forward. He will also tie these insights to the application and interview process, share tips based on his review of 1000s of application materials, and provide descriptions of what your career could look like in academia or government. Please bring questions, as he wants this to be a discussion as much as possible.
In this talk, I will discuss my experience as a math Ph.D. student at UCI (2015-2021), the job application process for postdoctoral research positions in math and differences and similarities between being a Ph.D. student and a visiting assistant professor.
In this talk, I will give a brief overview of my interdisciplinary career journey, in hopes of promoting and normalizing what may be deemed as an alternative path to applied mathematics. I’ll discuss some of my current research, which is focused on developing matrix- and tensor-decomposition methods for complex datasets, and will also introduce the audience to opportunities for mathematicians and computer scientists in government-sponsored research.
In this talk, I will describe my path from a liberal arts college to graduate school
at UCI to an academic career at a liberal arts college. First I will talk about my
experience in graduate school, and what led me to apply for positions in academia.
Next, I will describe the application process for academic jobs. Finally, I will discuss
my experience teaching at a liberal arts college.
Daniel will describe his path through internships, job applications, and the interview process. He will also give a brief introduction to The Aerospace Corporation and the role mathematicians and mathematics play at Aerospace and in the space industry in general.
We’ll introduce a common model framework for valuing and measuring risk for
options on pools of mortgages. In some market conditions this model does
not accurately match option market prices. Different ways of dealing with
this issue lead to different risk measurements. We’ll consider a “model
free” way of looking at risk through a local vol calculation, and use this
for comparison. As background we’ll introduce agency Mortgage Backed
Securities and some of their associated risk management issues.
At UCI he got a solid training in logic, then in algebraic geometry,
before finally getting his PHD in mathematical physics, in 2001, that
earned a department's Kovalevsky outstanding PhD thesis award. In the
postdoctoral period his interests switched to financial math. Now he is
the head of risk and quantitative opportunities for Catalina Asset
Management, the investment arm for the non-life insurance consolidator
Catalina Holdings. Before Catalina Michael was a Director in Quantitative
Risk Control at UBS Investment Bank. He has also had positions in the
financial industry at MSCI, PIMCO and Rimrock Capital Management, and he
has had faculty positions at Idaho State University and UC Santa Barbara.
Prior to the UCI PhD he got a BA in mathematics at the University of
Chicago.
After quickly explaining my mathematical research, I will mention my current involvement in the Institute for Mathematics and its Applications and reminisce on my graduate study experience at UCI.
