The importance of transcriptional control has been explored in a burgeoning line of research over several decades; nevertheless, we are still far from having a complete picture of the regulatory mechanisms of genes and non-coding RNAs, and their influences on different phenotypes and disease states of a cell. Recent shifts towards large-scale analyses of transcriptional regulation on a sequence and epigenetic level are at the forefront of research, mainly due to sequencing technology advancements and a deeper understanding of the fundamental regulatory processes involved.

Arriving at a better understanding of the influence of specific parts of the overall regulatory machinery on disease states is a high priority of the group’s research agenda.

We are seeking an enthusiastic student to join the group as a PhD student. Applicants must have a BSc(Hons) or MSc degree in a relevant discipline and a willingness to learn and apply new techniques and work in a team. Both local and international students are encouraged to apply.

The studentship covers all university fees and an annual tax-exempt stipend of NZ$22,000 for three years.

Sebastian Schmeier recently joined Massey University and started his own research group in Auckland, New Zealand, a city regularly ranked one of the most livable in the world. This is your chance to experience the amazing Auckland lifestyle and the excitement of joining a young new science team, while staying connected to world class scientific networks.

To apply for the post, please send a cover letter stating your interest in the position and why you think you would be a good candidate, a Curriculum Vitae, a copy of your academic transcript, a sample of your written scientific work, and the names of three referees. Applications will be accepted until the position is filled.

Enquiries and applications to Sebastian Schmeier (s.schmeier@massey.ac.nz).

We currently access an unprecedented knowledge on the basic components making up living systems. An ever growing number of new technologies are being developed with the capacity to systematically measure the behaviour of multiple cellular components, such as biochemical activities, biophysical properties, subcellular localization and interaction. These technologies produce large amounts of raw data that can be transformed into information by software and tools developed both in academia and industry. However, this biological information does not equal biological knowledge. As biology becomes large-scale, new methods have to be developed to integrate, visualize and query the large amounts of information available. This is usually beyond the expertise of experimental labs. The goal of this young computational systems biology group is to generate biological sense from the growing amount of biological data becoming available and turn biological information into biological knowledge. http://www.biw.kuleuven.be/m2s/cmpg/research/CSB

We seek a PhD student who will work as a computational biologist in the interdisciplinary project NATAR. Understanding the relationship between an organism’s genotype and phenotype remains one of biology’s fundamental challenges. In the project two model organisms, budding yeast and E. coli, will be exploited to better understand two complex genetic traits: ethanol and high temperature tolerance. For both organisms both natural variation and the outcomes of experimental evolution will be correlated with phenotypes. The first challenge in the project will be to identify which of the many variants in these genomes have functional effects. Then we will try to facilitate unravelling complex interactions between alleles, for example through functional gene networks that are based on a combination of published data. An important part of the generated data that underlies this project consists of high-throughput sequencing of DNA and mRNA of populations and isolates. For answering specific questions data integration with other data sources will be needed as well as the application of specific machine learning techniques. Basic molecular biology knowledge and basic programming skills are a prerequisite for this position. Experience with high throughput sequencing analysis methods, machine learning, protein interaction databases, perl/python scripting or BioconductoR are preferred. For more information contact prof. Rob Jelier (r.jelier@gmail.com) or prof. Vera van Noort (vera.vannoort@gmail.com). In your application please include a CV describing coursework, grades and previous research experience as well as a minimum of two letters of recommendation.

Starting date: from 1st of October 2013