Scientific programmer / software developer (bioinformatics)
We are looking for a scientific programmer / software developer to join our interdisciplinary microbiome research group at the Department of Biology.
The study of microbial communities and their genomic content (microbiomes) is a fast-growing research area. Ever-increasing amounts of data have become available to the scientific community over the past years. The analysis of such data has led to many impactul insights about the critical importance of microbes on Earth. We have learned much about their genomic diversity and functional capacity, the role they play in the health of animals and plants, and the ecological services they provide in the natural environment, for example. Such discoveries largely depend on extracting and integrating meaningful information from heterogeneous data sources, as well as rigorous statistical testing.
Are you interested in applying your algorithmic and programming skills to develop solutions that enable the analysis and interpretation of complex biological data?
The work in our reserach group revolves around ecological and evolutionary factors that determine the structure, function and diversity of microbial communities. To this end, we develop and combine bioinformatic and experimental approaches to integrate quantitative ‘omics data with contextual information to better understand and predict the role of environmental microorganisms and the underlying mechanisms of host-microbial homeostasis. In the past years, we have established large collections of metagenomic and metatranscriptomic resources and developed methodology to analyze such data in various ways. Examples include algorithms, tools and workflows i) to profile the taxonomic composition of microbial communities using metagenomic data or 16S rRNA sequences, ii) to integrate metagenomic and metatranscriptomic data, iii) to compare intra-specific populations at nucleotide level resolution, and iv) to localize genomic coordinates of inducible prophages in microbial genomes. We are continuously improving these methods and develop new ones whenever the need arises.
The group is well-positioned due to its involvement in collaborative project at both the national and international level. For more information, see:
Located at the Institute of Microbiology (www.micro.biol.ethz.ch) we benefit from an environment of complementary experimental expertise as well as infrastructure for high-performance computational analysis through the IT services of ETH Zurich. We are also affiliated with the Swiss Institute of Bioinformatics.
Reflecting our values, we strive to provide a diverse, open-minded and inclusive work environment, to nurture a culture of give-and-take, following the idea that the whole is more than the sum of its parts, and to value work-life-balance despite the competitive nature of a career in the life sciences.
You will support and/or lead the development of analysis workflows/pipelines as well as existing and new software tools for the analysis and interpretation of microbiome data (i.e., community genomics, transcriptomics, proteomics, metabolomics). Such data are either obtained from publicly available resources or generated in the context of the several collaborative projects the group is involved in. Common tasks will involve the design and execution of bioinformatic analyses, the programming of reproducible analysis workflows and/or development of software along with user-friendly documentation, in addition to providing expert advise to group-internal and external collaborators. We also provide training at the undergraduate and graduate student level and the postholder is expected to contribute to the organisation of courses and (co)supervision of students.
We expect a person that is technically skilled, allergic to bugs and proficient in the use of bioinformatics/computational tools. Her/his motivation is to provide cutting-edge support for ongoing research projects and to showcase the potential of her/his developments within the broader area of microbiome research. Given the interdisciplinary and collaborative nature of our work, a collaborative and goal-oriented mind set as well as excellent organisational and communication skills (oral and written) will be essential. A solid background in statistics and experience in machine learning is desirable.
Essential qualifications include:
- Postgraduate degree in (bio)informatics, computer science, computational biology or a related field
- Experience in the analysis of 'omics data such as high-throughput and long read sequencing and/or mass spectrometry-based (proteomics, metabolomics) data
- Proficient in Unix/Bash, Python and/or R programming, familiar with version control platforms
- Experience in working in high performance compute environments
- Excellent communication (oral and written), teamwork and organizational skills
The following additional qualifications may be advantageous:
- Knowledge in the use/development of software packages that help visualize and/or analyze scientific data (e.g., Shiny [R])
- Expertise in machine learning
- Experience in web development (e.g. Django, Angular, Rails or React)
- Background in microbial genomics/ecology/evolution
We look forward to receiving your online application with the following documents:
- A cover letter (one page) that demonstrates your motivation for the offered position
- A curriculum vitae including a list of publications and academic records
- Reference letters and/or names and contact information of at least two references
Please note that we only accept applications submitted through our online application portal. Incomplete applications and applications sent in via email or postal services will not be considered. The position is immediately available and the starting data is negotiable. The application review will begin on 5 of February 2021, and continue until the position is filled (or this advertisement has been removed).
Questions regarding the position should be directed to Prof. Dr. Shinichi Sunagawa.