Data Engineer / Technical Assistant (m/f/d)
fulltime - JobID: P0025V508
as soon as possible searched for Institute for Computional Biomedicine to wortk at the research group of Dr. Junyan Lu.
The position is limited to 3 years with option of further extension. Salary will be paied according to TV-UK.
We are looking for a data engineer/technical assistant to work within the SMART-CARE consortium, which aims at advancing precision oncology through mass-spectrometry proteomics/metabolomics data analysis and biomedical data integration. SMART-CARE consortium is a collaboration between University Hospital Heidelberg, Heidelberg University, Mannheim University of Applied Sciences, the German Cancer Research Centre (DKFZ) and European Molecular Biology Laboratory (EMBL). It aims to develop novel systems medicine approaches to battle cancer recurrence, using the integration of high-quality proteome and metabolome mass spectrometry data with other ‘omics and clinical data. The SMART-CARE consortium brings together clinical, mass spectrometry and computational expertise to tackle the urgent need for developing and establishing powerful and standardisable methods for proteome and metabolome analysis, as well as leveraging the power of multi-omics and machine learning to achieve high precision and robustness. The primary goal of the position is to establish and maintain the data analysis framework for pre-processing, quality control, documentation, and reporting of clinical omic data, with the focus on mass spectrometry proteomics and metabolomics data. You will also have the opportunity to shape your own research profile by pursuing research in developing innovative methods from mass spectrometry data analysis and integration.
Tasks and responsibilities
- Assemble suitable computational tools (or develop novel tools when necessary) into a streamlined and interoperable computation framework for end-to-end processing, QC, and reporting of clinical mass-spectrometry data. Ensure the robustness, reproducibility of the framework.
- Work closely with the research team and partners from the SMART-CARE consortium to integrate tools developed within the consortium into the framework and provide a user-friendly interface for internal and potential external users.
- Support the research team in locating and using relevant data resources, and in ingesting newly produced data.
- Assist the group leader in maintaining the research infracstructure for the group.
- Participate in project/data management tasks, including collaborative data production, analysis, and presentation.
Prerequisites
- Bachelor’s degree (or higher) in bioinformatics, informatics or computer science.
- Strong programming skills in R and/or Python, as well as the ability to acquire proficiency with modern big-data management systems (cloud, object storage) and with data analytical tasks.
- The tasks will also require the programmatic construction of web interfaces, for instance using tools such as Rmarkdown and shiny.
- Have good organizational and interpersonal skills. Fluent in German is a plus.
- Interests in computational algorithms, statistical analysis, or biological discovery are a plus.
What we offer
- Target-oriented individual further education and training opportunities
- Targeted training on the job
- Ticket for public transport
- Possibility of child care (crèche and kindergarten) as well as subsidy for holiday care for school children
- Active health promotion
- Company pension scheme
- Access to the university library and other university facilities (e.g. university sports)
Contact & Application
For further Information please contact Dr. Junyan Lu via
Interested?
Applications will be accepted until 4 weeks after publication. Please forward your complete application in a single pdf document – including a cover letter stating your motivation and research experience, your CV and the contact information of two to three referees by e-mail.
Medizinische Fakultät
Institute for Computational Biomedicine
Dr. Junyan Lu, Research Group Leader
Im Neuenheimer Feld 130.3
69120 Heidelberg