Interested in joining my group as a student or postdoc?
The primary objective of my research is to
produce new algorithms and
software that can dramatically improve
phylogenetic analysis (whether in linguistics or in biology),
as tested in simulation or on real data. Theoretical research
is often done at the same time, using probability theory to
predict performance under Markov models of evolution, but
then testing these predictions in simulation. Mathematical modelling
is also part of the work.
If you are a student who loves to design
algorithms, likes the challenge of developing
good heuristics for
NPhard optimization problems, loves to program, and enjoys
collaborations (especially with scientists!),
you may find this research area fun and
rewarding.
Absolutely no background in biology or linguistics is required.
Research in my lab requires
strong skills in
algorithm design and analysis and
software development.
In addition,
excellent interpersonal skills,
oral and written communication skills,
and a passion for research are also necessary.
Overall, the required technical skills or coursework can be
described by:
 Strong programming skills in several
programming languages, such as Java, C/C++, Python, Perl
and R, and ability to learn others
(essential)
 Upper division course in algorithm design
and analysis (essential)
 Upper division courses in graph theory,
statistics, and probability theory
(necessary, but can be obtained after joining)
Prospective undergraduate students:
I welcome undergraduate students from computational disciplines
(CS, ECE, Statistics, and Mathematics)
as research assistants, and can supervise projects that include
testing and developing new computational methods in phylogenomics,
analysis of biological datasets using different methods,
etc.
If you are interested in working with me, please note that
I do not take students
who are in their senior year except under
very unusual circumstances (e.g., when there is
a record of prior work on very similar projects).
Prospective graduate students:
To join my lab, you should first take
my graduate class in
Algorithmic Genomic Biology.
This course introduces students to computational
phylogenomics, and many
students do
research as a course project.
These research projects often result in
published journal and conference papers, and thus
are a great way to learn about the research area.
I work very closely with all of my graduate
students. The first semester is a
rotation, generally
spent on a specific research project in
collaboration with other students, so that
the new student can find out about
the research area.
For those students who have not taken
my graduate course, the first semester also
involves doing the homework problems from
the textbook.
After a semester as a
rotation student,
the student can decide about continuing
to do a PhD in my lab.
Please feel free to talk with my current or former students
about working with me; the list of students is
available here.
Prospective postdocs
If you are interested in joining the lab as a postdoc,
then you should have all the required skills and coursework
for graduate students (including programming skill,
discrete mathematics, probability theory, and statistics).
In addition,
you should have already published several peerreviewed
papers in algorithms for phylogenetics, or in very closely related
research (metagenomic analysis, multiple
sequence alignment, etc.).
I do not hire postdocs without prior research
publications in the same topics I work on.
Finally, you will need to provide three letters of
reference.
However, before applying for a postdoctoral position, please
make sure your research interests and mine are closely
aligned.
To find out more:
If you are interested in being my student or postdoc, please
first read a few of my recent papers.
Contact me by email and let me know
which of my papers you've read, what projects
you'd like to work on, and what your background
is (see above).
You may also want to read some of the
following introductory materials to this research area:

Computational Phylogenetics:
An introduction to designing methods for phylogeny
estimation, to be published by
Cambridge University Press in 2017.

Largescale multiple
sequence alignment and phylogeny estimation,
T. Warnow, 2013, in Models and Algorithms for Genome Evolution, Springer Computational Biology Series, C. Chauge, N. ElMabrouk, and E. Tannier, Editors.

Disk Covering Methods: improving the
accuracy and speed of largescale phylogenetic
analyses by T. Warnow (appeared as
``Largescale phylogenetic reconstruction,
in S. Aluru (editor), Handbook of Computational Biology, Chapman
& Hall, CRC Computer and Information Science Series, 2005).

The
Computational Phylogenetics in Historical Linguistics webpage.
 My list of papers (most downloadable) is
online.