Doctoral Candidate (DS) / PhD Position (m/f/x) Micromanufacturing Technology

Doctoral Candidate (DS) / PhD Position - EDM Machining-State Analysis from Discharge Signal Data

Position Details

Faculty of Mechanical Engineering, Professorship Micromanufacturing Technology at Technische Universität Chemnitz

Starting: 01.10.2026 (earliest, negotiable)

Employment: 100%, salary plus allowances package according to the Marie Skłodowska-Curie Actions (MSCA) – Doctoral Networks rules

Duration: 3 years

This position is one of 15 doctoral candidate positions of the MicroMan4Health doctoral network. Supervised by Prof. Dr. Andreas Schubert.

About the Network

MicroMan4Health focuses on developing data-centric micromanufacturing technologies for next-generation healthcare and MedTech applications. The network operates across 7 European countries (Belgium, Denmark, Italy, Germany, Slovenia, United Kingdom, Spain) and the United States of America, with secondments to numerous industrial companies.

Working Tasks

The PhD-project DC14 focuses on the development of an assisting tool for electrical discharge machining (EDM) to gain deeper knowledge on machining states and deposition characteristics from discharge signal data. The aim is to reduce process development iterations for EDM shaping with concurrent functionalization of surfaces by deposition of elements from electrode materials to realize antibacterial effects.

• Developing a data-driven tool for analysing real-time discharge signal data to gain deeper understanding of micro-EDM processing states and deposition-specific characteristics
• Correlating pulse voltage, current signals and discharge characteristics with material-removal behaviour as well as surface functionalization through deposition
• Enabling prediction of machining results and improving process stability with fewer experimental iterations
• Integrating antibacterial coating strategies to predict coating efficacy and long-term surface performance through intelligent data analytics
• Delivering validated methods applicable to machining medical implants and new tool–workpiece material combinations

Key Objectives

• Development of an algorithm to analyse discharge signals
• Building a secure dataset for new tool–workpiece material combinations enabling process-integrated antibacterial coatings
• Derivation of data-based strategies to reduce experimental iterations, ensure shape accuracy and assess removal and wear rates for medical-implant machining
• Validation of the approach and antibacterial effects in vitro

Secondments to industry and university partners support industrial validation, verification of process-detection concepts, and round-robin testing of the developed data-analysis framework.

The doctoral candidate will enrol in the doctoral student programme at Chemnitz University of Technology and will use research results for scientific publications and own qualification.

Required Qualifications

• Completed scientific university degree in Mechanical Engineering, Materials Engineering, Production Engineering or a related field in Science and Engineering or comparable disciplines, which gives access to the corresponding qualification level
• Experience with experimental research
• Very good knowledge (written & spoken) of the English language
• Strong motivation and ability to collaborate in an interdisciplinary and international team

Eligibility Conditions (MSCA)

• Candidates must not have lived in Germany for more than 12 months combined in the three years before October 2026 according to the mobility regulations of the doctoral network
• Candidates must not have obtained a PhD title elsewhere

Application Requirements

Please submit your complete application via the online application portal by 15.09.2026 (keyword 'Microman4Health-DC14-EDM').

Applications should include:

1. Motivation Letter: A letter (maximum 1 A4 page) addressing your strengths and qualifications in relation to the project
2. Complete Academic CV: A detailed CV including information about your education, current position, work experience (if any), employment gaps (if any), interests, extracurricular activities, international experiences, and projects demonstrating your programming/software skills, background knowledge relative to the project and level of expertise
3. List of Publications: If applicable, provide a list of your publications, including DOIs. Please do not include PDFs of the publications
4. Copies of Diplomas and Supplements: Include copies of your BSc and MSc degrees with diploma supplements
5. Transcript of Records: Provide transcripts for your BSc and MSc degrees. If you have not yet completed your Master's degree, include your available credits and scores, as well as a list of courses you are taking in the upcoming semester
6. English Summary of Master Thesis: A summary of your master thesis in English (maximum 1 A4 page, or 2 pages max when including a figure)
7. Proof of English Language Proficiency: Documentation demonstrating your proficiency in English (TOEFL, IELTS, …), if available
8. Reference Letter or Contact Details: A reference letter or the contact information for one reference who can provide a recommendation letter upon request

Application Information

Please note that, to ensure data security, applications submitted via email will not be considered. If you prefer a different application method or have general questions regarding the recruitment process, please contact Ms. Wagenitz (Tel. 0371/531-12210).

For applications and additional information about this research project and DC position, please contact the scientist in charge Mr. André Martin (Tel. 0371/531-39324).

Equal Opportunities

Chemnitz University of Technology aims to support women in particular and therefore expressly asks qualified women to apply. In the case of equal suitability, severely disabled persons or persons of equal status will be given priority in accordance with SGB IX.

Funding

MicroMan4Health is funded by the European Union's Horizon Europe research and innovation programme under Grant Agreement No. 101312169.