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Forschungszentrum Jülich, part of Germany’s prestigious Helmholtz Association, invites applications for a 4-year PhD position in AI-guided design of DNA nanostructures. This interdisciplinary project blends nanotechnology, artificial intelligence, and experimental biophysics to develop programmable, scaffold-free DNA tiles for advanced nanomaterials and artificial cell systems.
🔍 Job Details
| Title | Collaborative Doctoral Project (PhD) – AI-Guided Design of Scaffold-Free DNA Nanostructures |
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| Organization/Publisher | Forschungszentrum Jülich – Helmholtz Association |
| Work Location | Jülich, Germany |
| Research Field | Nanotechnology, Structural DNA Nanotechnology, AI-driven Molecular Design |
| Funding Info | Fully funded, 4-year position, TVöD-Bund salary (up to 100% E13) + bonuses |
| Application Deadline | 19 January 2038 |
| Posted Date | 12 August 2025 |
| Country | Germany |
| Researcher Profile | First Stage Researcher (R1) – PhD Candidate |
| Required Qualification | Master’s degree in Physics, Applied Mathematics, or relevant Engineering field |
| Required Experience | Programming, numerical modeling; interest in experiments; AI/ML experience advantageous |
| Salary Details | TVöD-Bund E13 (up to 100%) + 60% monthly bonus, annual leave, flexible arrangements |
| Apply Button | Apply Now |
Unlock the next frontier in nanotechnology with AI!
Forschungszentrum Jülich, a world-class research hub within the Helmholtz Association of German Research Centres, is offering a fully funded PhD position that merges structural DNA nanotechnology with machine learning to create programmable, scaffold-free DNA assemblies.
About the Project
DNA nanotechnology enables the design of all-DNA building blocks with atomic-level precision, making it possible to fabricate artificial cell mimics and new functional nanomaterials. This project focuses on scaffold-free DNA tile assembly, where custom-shaped 2D and 3D structures self-assemble from single-stranded DNA molecules.
However, predicting complex DNA structures remains challenging. This doctoral research aims to develop an AI-based digital twin—a predictive system that designs optimal DNA motifs for desired nano-tessellations. Using DNA thermodynamic data, coarse-grained simulations, and experimental results, you will train transformer-like AI models to guide nanostructure fabrication.
Key Responsibilities
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Conduct numerical simulations to generate AI training datasets.
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Develop AI models for predicting DNA secondary structures.
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Perform laboratory experiments for validation.
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Present findings at international conferences.
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Publish research in high-impact journals.
Ideal Candidate Profile
You are a motivated researcher with a Master’s degree in physics, applied mathematics, or a related engineering discipline. You have strong programming skills, an interest in lab work, and ideally some exposure to machine learning or high-performance computing.
Why Join Forschungszentrum Jülich?
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Cutting-edge infrastructure including top European supercomputers.
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International research environment with expertise in biophysics and soft matter.
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Professional growth via structured doctoral programs and networking.
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Flexible working arrangements and 30 days annual leave.
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Competitive TVöD-Bund salary plus bonuses.
This is more than just a PhD—it’s your chance to combine nanotechnology, AI, and experimental science to push the boundaries of nanoscale engineering.
Reference Links
Disclaimer: This information is based on the official posting from Forschungszentrum Jülich. Applicants should verify details via the official job link before applying.
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