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🚨 Postdoctoral Research Scientist in Computational Materials Design, Molecular Modeling & Machine Learning | Kiel University
Institution: Kiel University – Faculty of Engineering, Institute for Materials Science
Chair: Chair for Bioinspired Materials and Biosensor Technologies – Prof. Zeynep Altintas
📍 Location: Kiel, Germany
💼 Position Available: Postdoctoral Research Scientist
🔬 Research Areas: Computational Materials Design | Molecular Modeling | Machine Learning | Bioinspired Materials | Molecularly Imprinted Polymers | Nanocomposites | Biosensors | Molecular Recognition
The Chair for Bioinspired Materials and Biosensor Technologies at Kiel University is inviting applications for a Postdoctoral Research Scientist position focused on computational design of bioinspired materials, molecular modeling, and machine learning.
The position combines molecular mechanics, molecular dynamics, quantum mechanical calculations, and machine learning with experimental validation to develop advanced materials, synthetic receptors, molecularly imprinted polymers, nanocomposites, and functional interfaces.
🔬 Research Background
The research group works at the intersection of materials science, computational chemistry, molecular modeling, biosensor technologies, and artificial intelligence.
Research activities include:
- Computational design of synthetic receptors and bioinspired materials
- Molecular recognition and biomolecular interactions
- Molecular dynamics simulations of proteins, peptides, and polymers
- Quantum mechanical and QM/DFT calculations
- Molecular docking and free-energy calculations
- Molecularly imprinted polymers
- Nanocomposites and functional interfaces
- AI/ML approaches for materials discovery
- Computational design and optimization of advanced materials
- Integration of computational modeling with experimental validation
🧪 Postdoctoral Research Focus
The successful candidate will contribute to research in computational materials design, molecular modeling, and machine learning.
The research will involve:
- Molecular modeling of biomolecular recognition processes.
- Molecular dynamics simulations of proteins, peptides, polymers, and interfaces.
- QM/DFT calculations for molecular and materials systems.
- Development of computational workflows for materials discovery.
- Application of AI and machine learning approaches to molecular and materials design.
- Design and optimization of molecularly imprinted polymers and nanocomposite materials.
- Investigation of molecular interactions and functional interfaces.
- Integration of computational predictions with experimental research.
🔬 Research Methods & Approaches
Molecular Modeling & Molecular Dynamics
Apply molecular mechanics and molecular dynamics simulations to investigate biomolecular recognition, protein–ligand interactions, polymers, and functional materials.
QM/DFT & Computational Chemistry
Use quantum mechanical and density functional theory (QM/DFT) approaches to investigate molecular properties and guide materials design.
Molecular Docking & Free-Energy Methods
Apply molecular docking, advanced sampling techniques, and free-energy calculations to study molecular interactions and recognition.
AI & Machine Learning
Develop and apply machine learning and deep learning workflows for molecular and materials discovery.
Bioinspired Materials
Contribute to the computational design of synthetic receptors, molecularly imprinted polymers, nanocomposites, and functional materials.
High-Performance Computing
Utilize HPC and supercomputing resources for large-scale molecular simulations, computational chemistry, and machine-learning workflows.
🎯 Ideal Candidates
The ideal candidate should have a strong academic and research background in:
- Computational Chemistry
- Computational Biology
- Bioinformatics
- Computational Materials Science
- Molecular Modeling
- Materials Science
- Chemical Engineering
- Related computational or interdisciplinary fields
Candidates should have:
- A PhD in computational chemistry, computational biology, bioinformatics, computational materials science, or a related field.
- Demonstrated expertise in molecular modeling or computational materials research.
- Experience with computational methods such as MD, QM/DFT, docking, or molecular simulations.
- Strong programming skills, particularly Python.
- Interest in interdisciplinary computational and experimental research.
- A strong publication record.
- Excellent English communication skills.
💻 Preferred Research Experience
Experience in one or more of the following areas is desirable:
- Molecular Dynamics (MD)
- QM/DFT calculations
- Molecular docking
- Free-energy calculations
- Advanced sampling methods
- Machine learning and deep learning
- Molecular modeling
- Computational materials design
- Biomolecular recognition
- Molecularly imprinted polymers
- Nanocomposite materials
- High-performance computing
- Python-based computational workflows
Experience with GROMACS, AMBER, CHARMM, NAMD, or OpenMM is desirable.
Experience combining computational modeling with experimental validation will also be valuable.
🌟 What You’ll Gain
Successful postdoctoral researchers will have the opportunity to:
- Work on interdisciplinary research at the interface of materials science, computational chemistry, AI, and biosensor technologies.
- Develop advanced expertise in molecular modeling and simulation.
- Apply machine learning to materials discovery.
- Access high-performance and supercomputing facilities.
- Collaborate with researchers across materials science, engineering, computer science, and medicine.
- Develop and publish independent research.
- Contribute to research proposals and collaborative projects.
- Gain teaching experience in an international academic environment.
- Potentially pursue habilitation at Kiel University.
📌 Research Focus
The research program integrates:
- Computational Materials Design
- Molecular Dynamics
- Molecular Mechanics
- QM/DFT
- Molecular Docking
- Free-Energy Methods
- Machine Learning
- Deep Learning
- Bioinspired Materials
- Molecularly Imprinted Polymers
- Nanocomposites
- Functional Interfaces
- Biomolecular Recognition
- Biosensor Technologies
- High-Performance Computing
The selected postdoctoral researcher will contribute to computationally guided development of advanced materials and molecular systems, supported by experimental validation and interdisciplinary collaboration.
💼 Anticipated Responsibilities
The selected Postdoctoral Research Scientist will be expected to:
- Conduct molecular modeling and computational materials research.
- Perform molecular dynamics simulations of proteins, peptides, polymers, and interfaces.
- Apply QM/DFT and molecular docking approaches.
- Develop computational workflows for materials discovery.
- Apply AI/ML and deep-learning methods to molecular and materials systems.
- Design and optimize bioinspired materials and molecularly imprinted polymers.
- Analyze and interpret computational data.
- Collaborate with experimental researchers.
- Publish research findings in scientific journals.
- Contribute to research proposals and project development.
- Supervise students and contribute to teaching activities.
- Participate in interdisciplinary research collaborations.
📄 How to Apply
Interested candidates should submit their application through the Kiel University job portal.
📩 Application Contact
Email: abu@tf.uni-kiel.de
Job Portal: jobs.uni-kiel.de
Reference/Posting ID: 76f612f4746f60e09bf6b7d67ca721f0edee63dd0
📍 Position Details
Institution: Kiel University
Faculty: Faculty of Engineering
Institute: Institute for Materials Science
Chair: Chair for Bioinspired Materials and Biosensor Technologies
Supervisor: Prof. Zeynep Altintas
Position: Postdoctoral Research Scientist
Location: Kiel, Germany
Research Areas: Computational Materials Design | Molecular Modeling | Machine Learning | Bioinspired Materials | Biosensors | Materials Science
Key Skills: MD | QM/DFT | Molecular Docking | Free-Energy Methods | ML/Deep Learning | HPC | Python
Desirable Tools: GROMACS | AMBER | CHARMM | NAMD | OpenMM
Qualification: PhD in Computational Chemistry, Computational Biology, Bioinformatics, Computational Materials Science, or related field
Contract: 3-Year Full-Time Contract
Salary: TV-L E13
Teaching: English
Start Date: Earliest Possible
Application Deadline: 31 October 2026
Application Mode: Online Application
Contact Email: abu@tf.uni-kiel.de
Category
Postdoctoral Position | Computational Materials Science | Molecular Modeling | Machine Learning | Molecular Dynamics | QM/DFT | Computational Chemistry | Materials Science | Germany Jobs | Research Jobs | Postdoc Jobs | University Jobs
🏷️ Tags
#PostdoctoralPosition #PostdocJobs #KielUniversity #ComputationalMaterials #MolecularModeling #MachineLearning #MolecularDynamics #QMDFT
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