Postdoctoral position in phylogenetics

Tandy Warnow tandy at
Mon Sep 22 11:17:58 EST 1997

     Postdoctoral position at the University of Pennsylvania
           in Phylogenetics and Systematic Biology

The University of Pennsylvania has funding from the National Science
Foundation for a doctoral and postdoctoral training program in 
Computational Biology.  One of the foci of the program is
evolutionary biology and phylogenetics.

We  have funding for several postdoctoral fellowships, and
one of these fellowships may be awarded to an evolutionary biologist 
to work with Tandy Warnow, Co-PI of the Computational Biology program, 
and faculty member in Computer and Information Science.  
The salary for these fellowships is $40,000 annually, and are
renewable (subject to satisfactory progress) for an additional
year.  Generous equipment and travel support is provided.
The fellowship includes medical benefits.

This project is concerned with the development and testing of
new approaches for phylogeny estimation, especially on large
intractable datasets.  Experimental studies, algorithm design
and implementation, and analysis of real hard data sets, are
the specific agenda of the project.  Candidates for this specific
postdoctoral fellowship must exhibit exceptionally strong 
ability and accomplishments in both the biological and mathematical
sides of the problem, be a capable C programmer, and have publications 
already in phylogenetic studies.

UNLESS YOU SATISFY THIS CONDITION.  Conditions of support from NSF 
require these conditions.

Please apply directly to Tandy Warnow, and arrange for at
least three academic references to send letters of reference
(by email, preferably, and in plain text).  This position is
available now, but will be considered competitively within
the pool of applicants for postdoctoral positions
in the computational biology program.

Please send the following: 

           (a)  Completed application form (see below).
           (b)  Statement (maximum one page) of your research 
                interests, academic goals,  and why you are 
                interested in computational biology.
           (c)  Four letters of reference -- these should be 
                     sent directly by the referees.
           (d)  Curriculum vita.

For general information about the computational biology program, see
the information below.

                       Dr. Tandy  Warnow (Co-PI), 
                       Computational Biology Training Program
                       Department of Computer and Information Science
                       University of Pennsylvania
                       Philadelphia PA 19104-6389


    University of Pennsylvania Training Program in
            Computational Biology

The University of Pennsylvania has established an 
interdisciplinary training program for PhD students 
and postdoctoral researchers in computational biology. 
Areas of  interest include:
     biological databases, 
     multiple sequence alignment, 
     molecular evolution and phylogeny construction, 
     physical and genetic mapping, 
     sequence search and analysis, 
     statistical methods, 
     discrete algorithms and combinatorial 
         optimization in biology.

The research training program provides core training
in molecular biology and genetics, discrete algorithms,
mathematical modelling, and probability and statistics,
so that important biological problems can be addressed
effectively through a collaborative effort between 
researchers in these different fields. 
Advanced training draws on the expertise of the faculty, and
includes both advanced seminars and laboratory research

Participating faculty include the following:

Peter Buneman (Computer and Information Science):
Programming languages: applicative 
and functional languages, type systems.

Fan Chung (Mathematics):
Combinatorics and algorithms.

Susan Davidson (Computer and Information Science):
Real-time database systems: language 
support and formal methods for distributed real-time programs.

Arthur Dunham (Biology): Mathematical models at the interface 
of physiological ecology and population dynamics.

Joe Ecker (Biology):
Biochemical mechanisms involved in plant hormone signalling;
genome mapping.

Warren Ewens (Biology):
Mathematical population genetics.

Ellis Golub (Biochemistry, Dental School):
The relationship between protein sequence, structure and 

Greg Guild (Biology):
Sequential activation of ecdysone-regulated genes in 
Drosophila development; mechanisms of 
transcriptional regulation.

Aravind Joshi (Computer and Information Science):
Problems that overlap computer science and linguistics.

Sampath Kannan (Computer and Information Science):
algorithms in computational biology, complexity theory,
randomization and computation.

Haig Kazazian (Genetics):
The analysis of mutational mechanisms in humans.

Steve Liebhaber (Genetics):
DNA structure-function relationships.

Mitch Marcus (Computer and Information Science):
Natural language processing.

Max Mintz (Computer and Information Science):
Decision making under uncertainty.

Chris Overton (Genetics):
Genome informatics and biological databases.

Peter Petraitis (Biology):
Community ecology of marine ecosystems:
theoretical ecology.

David Roos (Biology):
Molecular genetics and cell biology of protozoan parasites; Host-pathogen 
interactions; Eukaryotic evolution.

David Searls (Genetics):
Linguistics of biological sequences; genome informatics.

Neil Shubin (Biology):
Evolution of developmental patterns; origins of the vertebrate limb; 
Comparative molecular and paleontological phylogenies.

Eero Simoncelli (Computer and Information Science):
Representation and analysis of visual imagery: 
distributed parallel representation and computation.

Rich Spielman (Genetics):
Genetics of susceptibility to complex human diseases.

Chris Stoeckert (Children's Hospital of Philadelphia):
Understanding the regulation of fetal and adult globin genes in human 

Santosh Venkatesh (Electrical Engineering):
computational learning theory.

Tandy Warnow (Computer and Information Science):
combinatorial and graph-theoretic algorithms for 
evolutionary tree construction.

All applicants (predoctoral and postdoctoral) to this interdisciplinary 
program should contact:

           Computational Biology Training Program
           Department of Biology
           University of Pennsylvania
           Philadelphia, PA 19104-6018
           compbio at

Admission to the predoctoral program requires acceptance
into a regular PhD program at the University 
of Pennsylvania. For application materials
contact one of the following:

Graduate Admissions
Department of Computer and Information Science
200 S. 33rd Street
University of Pennsylvania, Philadelphia PA 19104-6389

Graduate Admissions 
Department of Biology
University of Pennsylvania
Philadelphia, PA 19104-6018

Biomedical Graduate Studies (Molecular Biology)
240 John Morgan
University of Pennsylvania
Philadelphia, PA 19104-6064

Please return this form with the information filled out to 
          Computational Biology Training Program
          Department of Biology
          University of Pennsylvania
          Philadelphia PA 19104-6018
          compbio at

                  Computational Biology at Penn


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