PhD: Improving genome diagnostics by using and developing bioinformatic tools

Requirements

- We are looking for an excellent candidate with a Master’s degree in Medical Biology, Molecular Biology, Biomedical Sciences, Life Sciences, or in a related field.
- A background or interest in in bioinformatics, programming skills in R, Python, Java, C++ and/or perl, and experience is an advantage.
- You have experience with state-of-the art genomic technologies, such as single cell sequencing technologies, mRNA, DNA sequencing and others.
- You have affinity with genome diagnostic questions.
- You are creative, pro-active, enthusiastic, out-of-the-box thinking, and goal orientated with a strong ability to work independently.
- You are a skilled communicator who can work in teams with diverse professional backgrounds and can liaise between the worlds of computational biology and basic biology.
- Ability to integrate knowledge from the different areas of expertise required for the project.
- Good written and verbal communication skills in English at a level appropriate to scientific research.

Conditions of employment

- Mentoring, supervision and training in processing and interpreting a wide range of genomics/omics approaches.

- Access to a state-of-the art computational infrastructure.

- A stimulating translational research environment.

- A PhD position (32 - 36 hours a week) for a fixed period of 4 years.

Your salary will be a minimum of € 2.495,- gross per month in the first year and a maximum of € 3.196,- (scale PhD) in the final (4th) year, based on a full-time appointment. In addition, the UMCG will offer you 8% holiday pay, and 8.3% end-of-year bonus.
The conditions of employment comply with the Collective Labour Agreement for Medical Centres (CAO-UMC).

Department
Genetica
The department of Genetics performs research, genome diagnostics and patient care of genetic disorders. Our strategy aims at a broad application of genetics in general care (mainstreaming). We use next generation sequencing such as whole exome sequencing and whole genome sequencing and SNP typing to study the genomes, but also more innovative technologies such as long read sequencing and mRNA sequencing are being explored. Moreover we explore how bioinformatic algorithms can improve data interpretation.
The clinical question is central in our endeavors. This requires a close collaboration between laboratory, bioinformatics, geneticists and clinicians. Gene panel and whole exome sequencing is now mainstream in clinical practice. We are looking to improve the diagnostic yield, by developing new interpretation tools using artificial intelligence , and integrating mRNA analysis and phenotype in the genomic analysis.