Auf einen Blick
- Aufgaben: Engage in cutting-edge research in stochastic analysis and its applications.
- Arbeitgeber: Join TUD Dresden, a top-tier university focused on solving global challenges since 1828.
- Mitarbeitervorteile: Enjoy flexible hours, remote work options, and financial support for public transport.
- Warum dieser Job: Be part of a diverse, innovative team that values your growth and contributions.
- Gewünschte Qualifikationen: Must have a degree in mathematics or related field with knowledge of stochastic processes.
- Andere Informationen: Women and candidates with disabilities are encouraged to apply.
Das voraussichtliche Gehalt liegt zwischen 42000 - 60000 € pro Jahr.
The Center for Molecular Bioengineering (B CUBE, https://tu-dresden.de/cmcb/bcube), its partner institutions the Biotechnology Center (BIOTEC) and the Center for Regenerative Therapies (CRTD), together with the School of Science, the Carl Gustav Carus Faculty of Medicine, the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), and the Leibniz Institute of Polymer Research Dresden (IPF) provide a collaborative research environment at TU Dresden.
At the Center for Molecular Bioengineering (B CUBE), an institute of the Center for Molecular and Cellular Bioengineering (CMCB), the Chair of Biomimetic Materials (Prof. Dr. Nils Kröger, https://tu-dresden.de/cmcb/bcube/forschungsgruppen/kroeger) offers a position as Research Associate / PhD Student / PostDoc (m/f/x) (subject to personal qualification employees are remunerated according to salary group E 13 TV-L) starting as soon as possible. The position is initially limited to 2 years (PostDoc) or 3 years (PhD student) and comprises 100% of the weekly hours (PostDoc) or 65% (PhD student) with the possibility of extension, governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG). The role offers the opportunity to obtain a further academic qualification.
Tasks
The successful applicant will join the research project \“Elucidating the Structure-Function Relationship in Silicanins and their Role in Diatom Silica Morphogenesis\“, funded by the German Research Foundation (DFG). This project investigates the biological formation of functional 3D mineral structures (biominerals) and seeks to identify the genes and proteins involved in the morphogenesis of complex-structured biominerals. The Kröger group uses diatoms as a model system to unravel the molecular mechanisms underlying lipid‑bilayer‑mediated biomineralization. The applicant will employ state‑of‑the‑art biochemical, molecular genetic and cell‑biological tools to understand the role of silicanins, a large family of novel transmembrane proteins, in governing silica biomorphogenesis. The project involves close collaboration with the Structural Biology group of Prof. Raz Zarivach at Ben Gurion University, Israel, to determine the 3D structure of silicanins and silicanin‑based supramolecular assemblies.
Requirements
University degree (MSc) and, if applicable, PhD degree in biochemistry, molecular genetics, molecular cell biology or related fields. Strong research experience in protein biochemistry is preferred. Prior experience in genome engineering or mass spectrometry is advantageous but not required. Excellent writing skills with a proven track record of successful research are essential. Excellent communication skills in English are indispensable.
TUD strives to employ more women in academia and research and therefore expressly encourages women to apply. The university is a certified family‑friendly institution and welcomes applications from candidates with disabilities. If multiple candidates prove to be equally qualified, those with disabilities or with equivalent status pursuant to the German Social Code IX (SGB IX) will receive priority.
Application
Please submit your detailed application with the usual documents by December 15, 2025 (stamped arrival date or the time stamp on the email server of TU Dresden applies), preferably via the TU Dresden SecureMail Portal https://securemail.tu-dresden.de by sending it as a single PDF file to sandra.herrmann@tu-dresden.de or to:
TU Dresden, B CUBE, Herr Prof. Dr. Nils Kröger, Tatzberg 41, 01307 Dresden, Germany.
Please submit copies only, as your application will not be returned to you. Expenses incurred in attending interviews cannot be reimbursed.
TUD is a founding partner in the DRESDEN‑concept alliance.
Reference to data protection
Your data protection rights, the purpose for which your data will be processed, as well as further information about data protection is available to you on the website: https://tu-dresden.de/karriere/datenschutzhinweis.
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Research Associate / PhD Student / PostDoc (m/f/x) Arbeitgeber: Technische Universität Dresden (TU Dresden)
Kontaktperson:
Technische Universität Dresden (TU Dresden) HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Research Associate / PhD Student / PostDoc (m/f/x)
✨Tip Number 1
Make sure to highlight your experience in stochastic processes and their applications during the interview. Be prepared to discuss specific projects or models you've worked on, as this will demonstrate your expertise and fit for the role.
✨Tip Number 2
Familiarize yourself with the current research being conducted at the Institute of Mathematical Stochastics. This knowledge will not only help you understand their work better but also allow you to ask insightful questions during your interview.
✨Tip Number 3
If you have teaching experience, be ready to share examples of how you've engaged students in mathematics. Discussing your teaching philosophy can show your commitment to education and your ability to contribute to the institute's teaching efforts.
✨Tip Number 4
Since good German language skills are a requirement, consider taking a language course if you're not already proficient. Showing your willingness to learn German can set you apart and demonstrate your commitment to integrating into the university culture.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Research Associate / PhD Student / PostDoc (m/f/x)
Tipps für deine Bewerbung 🫡
Understand the Position: Make sure to thoroughly read the job description and understand the requirements for the Research Associate / PhD Student / Postdoc position. Highlight your relevant experience in stochastic analysis and financial mathematics.
Tailor Your Application: Customize your CV and cover letter to reflect your qualifications and experiences that align with the specific tasks and requirements mentioned in the job description. Emphasize your teaching experience and knowledge of stochastic processes.
Prepare Required Documents: Gather all necessary documents, including proof of academic qualifications, current transcripts, and a copy of your most recent thesis or a representative scientific publication. Ensure these are compiled into a single PDF file as requested.
Submit via TUD SecureMail Portal: Follow the application submission instructions carefully. Use the TUD SecureMail Portal to send your application by the deadline of January 7, 2025. Make sure to check that your application is complete before sending it off.
Wie du dich auf ein Vorstellungsgespräch bei Technische Universität Dresden (TU Dresden) vorbereitest
✨Prepare for Technical Questions
Make sure to brush up on your knowledge of stochastic processes and their applications. Be ready to discuss specific models you've worked with and how they relate to financial mathematics or machine learning.
✨Showcase Your Teaching Experience
Since the position involves assisting in teaching, be prepared to talk about your previous teaching roles. Highlight any innovative methods you used to engage students and how you contributed to their learning.
✨Demonstrate Interdisciplinary Understanding
TUD values interdisciplinary collaboration. Be ready to discuss how your research can connect with other fields and contribute to solving broader societal challenges.
✨Express Willingness to Learn German
If you're not fluent in German, express your eagerness to learn the language. This shows your commitment to integrating into the university culture and collaborating effectively with colleagues.