PostDoc in Computational Biology (f/m/x)
Full time
Neuherberg near Munich
Home Office Options
We are Helmholtz Munich. In a rapidly changing world, we discover breakthrough solutions for better health.
Our research is focused within the areas of metabolic health/diabetes, environmental health, molecular targets and therapies, cell programming and repair, bioengineering, and computational health. We particularly excel in the fields of basic research, bioengineering, artificial intelligence, and technological development.
Through this research, we build the foundations for medical innovation. Together with our partners, we seek to accelerate the transfer of our research, so that laboratory ideas can reach society and improve people’s quality of life at the fastest rate possible.
This is what drives us. Why not join us and make a difference?
In the past two years, the world has witnessed a revolution in RNA therapeutics, thanks to the popular COVID-19 vaccines. Besides their use as therapeutic molecules, nucleic acids as therapeutic targets are appealing over protein-centric conventional approaches to drug development because they expand the number of therapeutically addressable genes to theoretically all transcripts encoded in the genome. Finding new RNA targets requires mining large and complex genomic data, to gain a detailed understanding of the RNA regulome, the layer that controls gene expression at the RNA level. This involves RNA-protein interactions, which, among others, govern RNA cellular localization and RNA function.
Artificial Intelligence (AI) enables us to tackle the complexity of RNA biology by finding patterns in the data, and it has the great potential of shaping the future of RNA therapeutics. Long non-coding RNAs (lncRNAs) are a large group of genes with increasingly important roles in many cellular processes. They can function directly on chromatin to regulate gene transcription. LncRNAs are gaining increasing attention as potential therapeutic targets, due to their high tissue-specific expression and dysregulation in diseases such as those of the cardiovascular system, the leading cause of death worldwide.
In the Marsico's lab, Computational RNA Biology group, at the Computational Health Center, Helmholtz Munich, in Munich, Germany we are seeking a talented post-doc to join our team in the field of computational biology.
We believe that excellent research requires a range of different perspectives. Diverse teams reach better solutions and are more innovative in their research topics.
Establishing our Diversity Management Strategy demonstrates our commitment to ensuring an appreciative company culture based on mutual respect. We are also implementing diversity-sensitive processes throughout our whole organization.
Your tasks
This position focuses on machine learning for regulatory genomics, specifically related to RNA processes. As part of the TRR 267 Consortium 'Non-coding RNA in the cardiovascular system,' you will be involved in methodological research and contribute to various tasks.
Your primary responsibilities will revolve around advancing deep learning models of protein-RNA interactions, building upon existing methods developed within our lab. Additionally, you will have the opportunity to develop new AI tools that predict RNA subcellular localization, splicing patterns, and the impact of RNA modifications on RNA processes based on high-throughput genomic data generated within the Consortium.
In addition to your work with machine learning models, we expect you to contribute to the development and utilisation of bioinformatics pipelines. These pipelines will be instrumental in analysing diverse genomic data generated by the Consortium, including CLIP-seq data for protein-RNA interactions, bulk and single-cell RNA-seq data, and Massive Parallel Reporter Assays. Collaboration is a key aspect of this position, and we anticipate your active involvement in dissecting the molecular mechanisms of target long non-coding RNAs (lncRNAs) alongside experimental research groups.
Your profile
To be successful in this role, you should have a strong background in statistical modelling and machine learning, as well as bioinformatics. Proficiency in programming languages commonly used in bioinformatics and suitable for deep learning applications, such as Python, is essential. Knowledge of genomics and RNA biology, and previous experience with analysing genomic data will be advantageous.
The candidate must have excellent written and verbal communication skills, the ability to engage in independent thinking, be meticulous in their attitude towards work, and be a good team member. The candidate must also demonstrate scholarship through at least one published first-author manuscript.
Benefits
Since 2005, we hold the TOTAL E-QUALITY award for exemplary action in the sense of an equal-opportunity organizational culture.
Helmholtz Munich is actively committed to diversity and inclusion in practice and is sustainably committed to equality.
The Diversity Charter has set itself the goal of promoting diversity in the world of work. By signing the charter, we commit ourselves to create an appreciative working environment for all employees.
If you fulfil all the requirements, you may be eligible for a salary grade of up to E 13. Social benefits are based on the Collective Wage Agreement for Public-Sector Employees (TVöD). The position is (initially) limited to 4 years, under certain circumstances an extension can be arranged.
We are committed to promoting a culture of diversity and welcome applications from talented people regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical abilities, religion or age. Qualified applicants with physical disabilities will be given preference.
If you have obtained a university degree abroad, we will require further documents from you regarding the comparability of your degree. Please request the Statement of Comparability for Foreign Higher Education Qualifications as early as possible.
Interested in applying?
- a motivation (cover) letter specifically addressed to our group
- CV
- contact details of two referees
