Summary
The Faculty of Chemistry and Food Chemistry, Chair of Inorganic Chemistry I at TUD Dresden University of Technology is offering a full-time, EU-funded project position for a Research Associate / Postdoc (m/f/x). The successful candidate will work on developing adsorption databases, AI-supported algorithms for material selection, and machine learning process simulations for fluorinated gases (F-gases) in advanced crystalline adsorbents.
Postdoc Opportunity: Computational Chemistry & AI at TUD Dresden University, Germany
Designation
- Research Associate / Postdoc (m/f/x)
Key Job Details
| Attribute | Details |
| Position Title | Research Associate / Postdoc (m/f/x) |
| Institution | TUD Dresden University of Technology |
| Faculty / Chair | Faculty of Chemistry and Food Chemistry / Chair of Inorganic Chemistry I |
| Salary Group | Remunerated according to salary group E 13 TV-L |
| Employment Period | November 1, 2026 – October 31, 2028 (Fixed-term) |
| Funding | Funded by the European Union |
| Reference Number | w26-187 |
| Application Deadline | August 31, 2026 |
Research Area
- Computational Chemistry & Materials Science
- Gas Adsorption & Porous Materials
- Data Science, AI & Machine Learning for Material Selection
- Process Simulation & Environmental Technologies
Location
- Dresden, Germany (TUD Dresden University of Technology)
Eligibility / Qualification
- Degree: Very good university degree (M.Sc. or equivalent) in chemical engineering, materials sciences, chemistry, computational science, physics, data science, or a closely related field.
- Specialization & Skills:
- Specialization in computational chemistry, data science, porous materials, and FAIR principles.
- Practical experience in simulating and analyzing adsorption data and managing databases.
- Strong programming skills and deep knowledge of porous materials/adsorption processes.
- Early Career Criteria:
- Junior researchers who completed studies or PhD no more than 6 years before April 1, 2026 (extension of 2 years per supervised child born between completion and proposal submission).
- Specific conditions apply regarding previous ESF/ESF Plus funding (doctoral project must be completed or dissertation submitted).
- Track Record & Soft Skills:
- Excellent individual performance criteria (e.g., publications resulting from Master/PhD thesis, awards).
- High motivation for interdisciplinary collaboration (especially Life Cycle Assessment – LCA) and environmental digitalization.
- Excellent written and verbal communication skills in English.
Job Description
- Database Creation: Establishing a comprehensive database for adsorption data of fluorinated gases (F-gases).
- Gas Adsorption Simulation: Simulating gas adsorption isotherms for relevant F-gases in advanced crystalline adsorbents, taking into account competitive water adsorption (humidity) effects.
- AI & Machine Learning: Developing AI-supported algorithms for material selection in close feedback loops with experimentalists, alongside machine learning for process scaling.
- System-Level Simulation: Process simulation of adsorption processes at the system level.
- Interdisciplinary Collaboration: Close interaction with partner groups within the joint project, active participation in project meetings, and integration into contributing networks.
- Documentation & Teaching: Publishing scientific articles, presenting at national/international conferences, and contributing to teaching and student supervision.
How to Apply
- Prepare a detailed application containing standard application documents quoting reference number w26-187.
- Applications must be submitted exclusively by email as a single combined PDF file to:
- Email:
sekretariat-ac1@mailbox.tu-dresden.de
- Email:
- Submissions via the TUD SecureMail Portal are preferred.
Data Protection Note: Information regarding data processing rights is available on theTUD Data Protection Page.
Last Date for Apply
- August 31, 2026 (stamped arrival date of the time stamp on the email server of TUD applies)








