evolutionary genetics of sexual dimorphism

Job Description:

A Ph.D. student position is available beginning February 2017 to study the
evolutionary genetics of sexual dimorphism. The position is based in
Lausanne, Switzerland, at the Swiss Federal Institute of Technology (EPFL),
supervised by Dr. Brian Hollis. The project will combine experimental work
in Drosophila melanogaster with molecular genetic and bioinformatic
approaches (e.g. population genomics, genome-wide association, expression
profiling) to better understand the evolution and genetic basis of
differences between the sexes. There is considerable scope for the Ph.D.
student to shape the project and develop his or her own research questions.

Highly motivated candidates with a Masters degree (or a Bachelors degree for
applicants from the U.S.) in biology, computational science, or related
disciplines are encouraged to apply. Previous experience with Drosophila is
a plus, but not strictly necessary. A background and interest in
quantitative biology is essential, along with excellent writing and
communication skills. 

The EPFL is a dynamic university ranked among the top research institutions
in Europe and offers a rich international environment with English as the
working language. The university's core facilities provide state of the art
sequencing and computational resources. Lausanne is located on Lake Geneva,
a short ride from the Alps, with an attractive climate and standard of
living.

Applications are due by November 15th, 2016. You can learn more about the
School of Life Sciences at EPFL at http://sv.epfl.ch and how to apply to the
Molecular Life Sciences PhD program at http://phd.epfl.ch/edms/en. 

For informal inquiries, feel free to send me a message at
brian.hollis@epfl.ch. 

Dr. Brian Hollis

School of Life Sciences 

École Polytechnique Fédérale de Lausanne

Lausanne, Switzerland 

brian.hollis@epfl.ch

Requeriments :

• M.Sc. or higher Degree in Bioinformatics
• M.Sc. or higher Degree in Computer Science

Skills :

• Bioinformatics
• Biology

Areas :

• Bioinformatics

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