PhD position: High-Throughput Development of Chemical Conversion Treatment for Light Metals

Hereon; Geesthacht; On-site; EUR 48,000 - 60,000; Full time

Benefits offered by this job

6 weeks holiday

Flexible work

PhD Buddy Program

Canteen on campus

Public transport subsidy

Job summary

Hereon is inviting a PhD student to develop high-throughput, robotic experimentation methods for chemical conversion treatments on light metals. The project blends experimental screening with AI-assisted data analysis, aiming to uncover mechanisms and translate them into design rules for improved coatings.

Collaboration with computation and materials science teams is integral. You will publish in journals, present at conferences, and contribute to FAIR datasets while benefiting from a dynamic

Qualifications

• Completed master's degree in chemistry, electrochemistry, materials science, computational materials science or a related field.
• Solid experimental skills in chemical laboratories and confidence in quantitative data analysis using appropriate software.
• Experience with corrosion protection, including chemical conversion coatings for light alloys (Mg, Al or Zn).
• Experience with electronic lab notebooks, FAIR data, databases or machine learning.
• Curiosity about automation and AI, and motivation to work at the interface of experiment and computation.
• Very good English; knowledge of German preferred but not mandatory, language learning supported.

Responsibilities

• Develop and validate experimental methods for accelerated screening of chemical conversion treatment formulations.
• Translate these methods into automated high-throughput workflows on our existing robotic testing platform.
• Work with computational scientists to build large, machine-readable datasets for AI-assisted discovery.
• Uncover mechanisms behind adhesion promotion and corrosion protection and turn them into design rules for next-generation coatings.
• Publish results in leading journals, present at international conferences, write project reports, and contribute to open, FAIR datasets.

Skills

Experimental skills

Data analysis

Corrosion knowledge

Lab notebooks

Machine learning

English proficiency

Education

Master's degree in chemistry or related field

Job description

PhD position: High-Throughput Development of Chemical Conversion Treatment for Light Metals

Aluminium and magnesium alloys are key to lighter vehicles, aircraft, drones and consumer goods but only if they are safe and durable, reliably protected against corrosion. Chemical conversion coatings are one of the most effective and commercially successful ways to do this. They protect the metal and help paint adhere to it. Yet finding better, environmentally friendly formulations is still largely a matter of trial and error. The number of possible formulations is virtually infinite, so we do not test them one by one. At the Department of Electrochemistry and Big Data, we run a robotic high-throughput testing platform combined with machine learning for AI-assisted discoveries. We are offering a 3-year position, as soon as possible, as a PhD student in the quickly developing field of high-throughput and robotic experimentation in materials science.

• Develop and validate experimental methods for the accelerated screening of chemical conversion treatment formulations
• Translate these methods into automated high-throughput workflows on our existing robotic testing platform
• Work side by side with our computational scientists to build large, machine-readable datasets for AI-assisted discovery
• Uncover the mechanisms behind effective adhesion promotion and corrosion protection, and turn them into design rules for next-generation coatings
• Publish your results in leading journals, present at international conferences, write project reports, and contribute to open, FAIR datasets

Your profile

• A completed master's degree in chemistry, electrochemistry, materials science, computational materials science or a related field
• Solid experimental skills in chemical laboratories and confidence in quantitative data analysis using appropriate software
• Experience with corrosion protection, including chemical conversion coatings for light alloys (Mg, Al or Zn)
• Experience with electronic lab notebooks, FAIR data, databases or machine learning
• Curiosity about automation and AI, and motivation to work at the interface of experiment and computation
• Very good English, knowledge of the German language is preferred but not mandatory, we support language learning

Content-related enquiries regarding this position can be directed to [e-mail].

Our offer

• A research topic with real industrial relevance, at the frontier of lab automation and Al-driven materials discovery
• A doctorate awarded by Hamburg University of Technology, TUHH, our partner university
• Access to state-of-the-art (robotic) labs, unique scientific and technical infrastructure
• Access to a large international research and industrial network
• Funding for conferences, summer schools and courses needed or research stays
• An exciting job in a research center with around 1,000 employees from more than 60 nations
• International Welcome Office with guest accommodation
• 6 weeks holiday per year; company holidays between Christmas and New Year's Day
• Social benefits according to the collective agreement of the public service and remuneration up to EG 13 (according to EntgO Bund)
• Very good work-life balance; options for mobile and flexible work
• A green campus on the Elbe River, well-connected with Hamburg (public transport), subsidy for the Deutschlandticket if certain conditions are met (job ticket), charging facilities for electric vehicles
• PhD Buddy Program
• Family-friendly company policy with childcare facilities, e.g. nursery/kindergarten close to the company
• Operational Health Management, e.g. Employee Assistance Program (EAP)
• A varied offer in the canteen on campus

Severely disabled persons and those equaling severely disabled persons who are equally suitable for the position will be considered preferentially within the framework of legal requirements.