Open Positions

Support of applicants for the SNF Eccellenza Professorial Fellowship, the SNF PRIMA funding program and the ERC Starting Grant in the field of "Biomedical Modeling"

The DQBM announces opportunities for applicants who seek to establish their own research group by obtaining independent third-party funding (SNF Eccellenza Professorial Fellowships, SNF PRIMA grant program and/or ERC Starting Grant Program (ERC-StG)). Successful candidates may be invited to negotiate an independent Assistant Professorship for a period of 5 years. To complement the independent external funding, the DQBM will provide laboratory facilities, administrative and financial support and a first-class scientific environment.

The DQBM fosters research and education at the interface of biomedical research, biotechnology, and computational biology, to develop the foundations of next-generation precision medicine. The exploration of novel tools to extract knowledge from experimental quantitative data sets will accelerate the precision medicine revolution. For the forthcoming ERC/SNF application rounds, we particularly encourage proposals that match the following profile:

The Assistant Professorship will focus on the (multiscale) modeling of disease processes, using e.g. statistical interference methods, differential equations, neural network based methods or similar approaches, with the aim of conducting computer-assisted simulation experiments for the dynamic prediction of processes in multicellular systems. Such systems include, but are not limited to, immune systems, tumor micro-environments, neural circuits and microbiomes, taking into account spatial (3D) relationships. Further research interests could include system dynamics, perturbations, and evolution, such as evolutionary dynamics in chronic infections and tumor development, as well as prediction of complex emergent behavior resulting from multicomponent interactions, as seen in protein assembly and aggregation.

The Assistant Professorship is designed for a scientist with strong methodological expertise in the fields of Computer Science, Statistics, Mathematics or (Bio-)Physics, and excellent research experience in modeling quantitative systems data. Furthermore, the supported candidate is expected to have the ambition to establish a strong independent research group with an international profile, as well as the willingness to synergise with the current research groups at the DQBM. In addition to research activities, the Assistant Professorship will contribute to teaching in the quantitative biomedicine curriculum.

The supported Assistant Professorship offers major opportunities for establishing a first-class computational research program in the field of biomedical modeling in collaboration with numerous partners and institutions in Zurich, including the University Hospitals of Zurich and the Bioinformatics Hub at the LOOP Zurich.

The University of Zurich is an equal opportunity employer and strives to increase the percentage of women in leading positions. Therefore, qualified female researchers are encouraged to apply.

How to apply:
Applicants should submit their application via the UZH job portal in a single pdf that includes:
-   A 1-page personal statement on why you are interested in joining our new, interdisciplinary department;
-   A 2-page research plan for the next 5 years;
-   A full CV highlighting your academic track record;
-   Contact details of 3 referees who can be contacted for recommendation letters.

The deadline for applications is 30 June 2021. Short-listed candidates will be informed by mid-August 2021 and invited to present their past achievements and research proposal during a symposium at the DQBM in September 2021. Final support decisions will be communicated in October 2021.

Further information: Prof. Dr. Bernd Bodenmiller (head.department@dqbm.uzh.ch)
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Senior computational staff scientist 100%

08.01.2021

The Bodenmiller lab is recruiting a senior computational biologist or bioinformatician to support the analysis of high-dimensional and spatially resolved single-cell data.

For more information, please see the full ad here
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Genomic Data Scientist 100%

20.11.2020
The Polymenidou lab is looking for a genomic data scientist to work closely with our experimental team to analyse and explore a large collection of high-throughput sequencing data. Experience in RNA-seq data analysis, including bulk transcriptomics, splicing analysis and single cell analysis is required. The ideal candidate will also have expertise in analyzing high-throughput sequencing datasets to determine the function of RNA-binding proteins, including CLIP-sequencing and related methodologies.

The successful candidate will be fully integrated in both the Polymenidou lab and the Robinson teams. The candidate will, therefore, combine work in neurodegeneration and RNA biology (Polymenidou) with statistical methods and data science tools (Robinson).

For more information, please see the full ad here
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Computational Master Student Projects in the Krauthammer lab

Flexible starting date

The Krauthammer lab is currently looking for Master’s students in the field of bioinformatics for the following topics:

Analyzing the effects of DNA secondary structure on the mutational pattern in cancer.
The student will analyze the relationship between mutational patterns detected in various cancer types and the locations of non-B-DNA secondary structures in the human genome. The student should have basic experience with Unix systems and some experience with at least one scripting language (e.g. Python, R or bash). Prior experience with genomics software (mappers, samtools or variant callers) is an advantage.
Mapping structural variation in cancer.
The student will use genome sequencing data in order to discover novel structural variants in various cancer types (melanoma, colorectal carcinoma, lung cancer, etc.). The clinical significance of the novel and already known structural variants will also be evaluated using genome annotations. The student should have basic experience with Unix systems and some experience with at least one scripting language (e.g. Python). Prior experience with genomics software (mappers, samtools or variant callers) is an advantage.

Applications can be done by sending a CV to this e-mail along with a short description of the student’s motivation to join our lab.

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Master Student positions in the Bodenmiller lab