Incoming Scientia Fellows (Postdoc positions) available
This call is open until April 30, 2020. We are looking for ambitious candidates interested in formulating their own research projects together with us as the host. The fellowships are available within three different subfields within the thematic area of bioinformatics: Precision medicine, Genome dynamics and Microbiome informatics. Descriptions and contacts for each thematic area can be found below. One position will be offered under each thematic area. If you would like to apply for one of these positions, please send an email to the contact points below for further instructions on how to apply.
Thematic area: Bioinformatics:
Subfield 1: Precision medicine
Precise patient stratification is a prerequisite for successful use of targeted therapies and immune therapies. An increasing number of clinical studies aim to select targeted drugs for cancer patients based primarily on the molecular characteristics of the tumours, and improved molecular stratifications are greatly needed. Leveraging of prior knowledge resources (databases and ontologies) is frequently critical for successful results. A combination of unsupervised and supervised analyses is further typically required to improve classifications, and a major challenge is the limited number of cases available for training compared to the number of explanatory variables available. Over the last decade, a range of new statistical methods has been developed for class prediction based on high-dimensional covariates. Deep learning and novel machine learning methods in general are central keywords in this context. The research focus for this area is the adaptation and further development of such methodologies to facilitate clinical applications in the cancer field. This thematic area is based on existing strong interactions with Norways foremost cancer research institute (at Oslo University Hospital).
Keywords: Deep learning, cancer bioinformatics
Subfield 2: 3D Genome Dynamics
Recent advances in high-throughput sequencing technologies allow for unprecedented characterization of the genome. Yet, most genomic studies ignore how DNA is dynamically organized in 3D space inside the nucleus. Such information is, however, crucial to understand gene (dys)-regulation in healthy and pathological states. Computational
modelling and simulation have proven extremely fruitful to characterize 3D genome dynamics at multiple levels. Dynamic structural 3D models of whole genomes have revealed spatial and temporal regulation of Topologically Associated Domain (TAD) positioning during cell differentiation. At more local scales, loop-extrusion modelling can predict with high accuracy the effect of mutational alterations of boundaries between TADs. The research focus for this area will be to develop new computational methodology to explore the dynamics of 3D genomes in time – in essence providing a four-dimensional (4D) view of the genome. The research will synergize with existing efforts to explore how the 3D genome relates to cancer development and immune regulation across departments at the University of Oslo.
Keywords: Epigenetics, Hi-C, chromatin structure, loop-extrusion, transcriptional regulation, 4D genomics, statistical genomics
Subfield 3: - Microbiome bioinformatics
The importance and impact of the microbiome for human health have become increasingly evident over the last decade. Several studies have established the relationship between the human microbiome and cancer as well as infectious, autoimmune and mental diseases. Advances in sequencing technologies have enabled us to investigate the metagenome and metatranscriptome of the microorganisms in samples from such diverse sites as the human body, food, animals, water, soil, and the built environment. Organisms that were previously almost impossible to culture have now become observable. Microbiome research is therefore also crucial for evolutionary studies and discovery of microorganisms in extreme environments. The taxonomic composition may be studied using amplicon sequencing (e.g. 16S or 18S rRNA), while whole-genome approaches allow further details including the active gene functions to be explored. Metabolomics may provide further insight into the biological processes. Our research concentrates on several aspects of microbiome bioinformatics, including development of new or improved analysis pipelines, as well as algorithms and tools for taxonomic classification, removal of noise and errors, and sequence comparison in general. We invite the Research Fellow candidate to think beyond the taxonomical classifications and gene function prediction and develop methods for holistic microbiome approaches.
Keywords: Microbiome bioinformatics, metagenomics, amplicon sequencing, taxonomic classification, metabolomics, algorithms
This is a funding mechanism offered in association with the Medical Faculty.For more information on the funding mechanism, visit the Scientia Fellows II programme - Call 2.