Population genetics seeks to describe the distribution of and the change in allele frequencies in natural and domestic populations. It attempts to explain evolutionary phenomena such as adaptation, differentiation, and speciation. As genotypes play a crucial role in determining phenotypes, the major challenge of population genetics has been the development of a theory that describes, with the help of Mendelian and non-Mendelian genetics, the interplay of evolution at the genotypic and phenotypic level.
Traditionally, population genetics has been often subdivided into two relatively isolated fields: complex mathematical models with limited connection to data and experimental work using only simplistic theory. In the future, it will be essential to reduce this isolation because of the dramatic changes of experimental designs due to modern technology and the flow of new data. A steadily growing number of fully sequenced genomes are available and the importance of natural variation has been recognized by such genome projects. With the technological tools available to provide genetic information on natural populations to the highest level of resolution, the interpretation of natural variation is about to become one of the primary research avenues in the present attempts to establish concrete links between genotypes and phenotypes. Computer simulations and new statistical methods are becoming increasingly important. In addition to the undoubted enormous benefit for basic research, the interpretation of natural variation will also be of central importance for many applied disciplines, such as conservation genetics, animal and plant breeding, and medicine.
The Vienna Graduate School of Population Genetics has an outstanding faculty of both theoretical and experimental population geneticists, functional biologists, and statisticians. Under their supervision, graduate students will learn how to bridge the realm of theoretical and experimental population genetics in an explicitly interdisciplinary and collaborative approach using bioinformatics, statistics and validation of hypotheses through functional genetics.
Prospective students could either have a background in theoretical, computational or experimental biology. The nature of the PhD program requests a strong desire for interdisciplinary and interactive research.