David Miller
Program Director in Mathematical Methods, Computational Modeling, Data Visualization, and Science Games
- Role
- Program Director at National Cancer Institute (NCI)
- Location
- Washington, DC, US
- LinkedIn followers
- 500 followers
About David Miller
Program Director in NCI’s Division of Cancer Biology; 20••••15 Science & Technology Policy Fellow. Dave manages a research grants portfolio in mathematical modeling, computational methods, data visualization, and interactive tools development for cancer biology. Dave\'s research training was in physics, with a focus on methods development for systems biology. Dave currently leads the data visualization activities for the Cancer Moonshot and is active in the NCI’s Informatics Technology for Cancer Research (ITCR) program. Previously as an Science and Technology Policy Fellow at NIH, Dave led the Targeted Software Development program for the NIH’s Big Data to Knowledge (BD2K) initiative. Additional program-relevant interests include emerging areas of cell fate prediction methodologies, data interaction paradigms, data analysis games/interactive media, and math theoretical methods for cancer biology. Dave completed his Ph.D. in Physics at Drexel University (2008), followed by a postdoc in computational toxicology at the US Environmental Protection Agency’s National Center for Environmental Assessment (20••••13).
Experience
Program Director
National Cancer Institute (NCI)
Aug 2013 — Present · Rockville, MD, US
Extramural funding and grants management across a broad swath of NIH-supported research including data science, software development, crowdsourcing, research games & interactive media, mathematical modeling and systems biology.
Education
Drexel University
M.S., Physics
2002 — 2004
University of Aberdeen
Differential Equations, Epidemiology, Pictish Art & History
The College of Wooster
B.A., Physics
1998 — 2002
Drexel University
Ph.D., Physics, Computational Biophysics
2004 — 2008
Skills
- Computational Methods
- Science
- Biochemistry
- Computational Biology
- Physics
- Biophysics
- Research
- Scientific Computing
- Mathematical Modeling
- Latex
- Teaching
- Scientific Writing
- Data Analysis
- Systems Biology
- Molecular Biology
- Statistics
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