Research Associate
Reference number: 2024-0345
- Heidelberg
- Full-time
- Proteomics Core Facility
“Research for a life without cancer" is our mission at the German Cancer Research Center. We investigate how cancer develops, identify cancer risk factors and look for new cancer prevention strategies. We develop new methods with which tumors can be diagnosed more precisely and cancer patients can be treated more successfully. Every contribution counts – whether in research, administration or infrastructure. This is what makes our daily work so meaningful and exciting.
The Proteomics Core Facility at the German Cancer Research Center (DKFZ) is seeking a
We are looking for a skilled and motivated Proteomics Research Associate with expertise in data analysis and mass spectrometry-based proteomics to join our team from March 2025. In this position you will play a key role in an interdisciplinary team focused on advancing proteomics and bioinformatic methods. The ideal candidate will be proactive, adaptable, and committed to continuous learning and technical skill development. Strong interpersonal and communication abilities are essential, along with a proven ability to collaborate effectively within a team. We seek someone who can present scientific data and concepts clearly in both internal meetings and at conferences, and who will represent the facility with professionalism. The role also holds the possibility for professional growth by offering the opportunity to take over management responsibilities in the future.
Your Tasks
- Providing expert support in project design and data analysis to ensure high-quality service for facility users.
- Collaborating closely with our bioinformatics team to co-develop and test new tools and analysis workflows that enhance facility capabilities.
- Engaging in collaborative projects with scientists across DKFZ, participating in consortia, and contributing to educational activities.
Your Profile
- Master's degree in a relevant scientific discipline (e.g. mathematics, physics, bioinformatics, biology, molecular biology, computational biology, or a related field), preferred with a PhD afterwards
- Advanced theoretical knowledge and practical skills in all aspects of omics data processing and integration are essential; experience with programming languages such as R, Python, or similar is highly desirable
- Proficiency in data analysis software tools specific for proteomics (e.g. MaxQuant, Spectronaut, Skyline, DIA-NN, Perseus) and data management platforms
- Comprehensive knowledge of qualitative and quantitative methods for protein and post-translational modification analysis using LC-MS/MS workflows
- Strong written and oral communication skills to facilitate collaboration with a diverse research community and faculty members
- Ability to assist with grant writing to support core facility development
- Experience with multi-omics integration (combining proteomics with genomics, transcriptomics, or metabolomics) is an advantage
We Offer
Excellent framework conditions: state-of-the-art equipment and opportunities for international networking at the highest level
30 days of vacation per year
Flexible working hours
Remuneration according to TV-L incl. occupational pension plan and capital-forming payments
Possibility of mobile work and part-time work
Family-friendly working environment
Sustainable travel to work: subsidized Germany job ticket
Unleash your full potential: targeted offers for your personal development to further develop your talents
Our Corporate Health Management Program offers a holistic approach to your well-being
Are you interested?
Then become part of the DKFZ and join us in contributing to a life without cancer!
Dr. Dominic Helm
Phone: +49 (0)6221/42-1811
We are convinced that an innovative research and working environment thrives on the diversity of its employees. Therefore, we welcome applications from talented people, regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical ability, religion and age. People with severe disabilities are given preference if they have the same aptitude.