working in a lab

Jobs & Training

We employ scientists in chemistry, engineering, physics, materials science, and mathematical modelling as well as staff in administrative and technical positions.

Vacancies and PhD Positions

Most of our current vacancies and PhD positions are posted on the KIT jobs page. For details on our PhD positions you may contact Patricia Jaeger or Christine Fischer. Vacancies not posted on the KIT website are included below.

Bachelors or Masters Thesis

Because we are an institute within the Karlsruhe Institute of Technology (KIT) and have close connections to other universities (including Darmstadt, Münster, Ulm, Gießen, Basel, and Strasbourg), we can supervise bachelor's or master's theses. To apply, please contact our research unit chairs and research groups.

PhD position funded by Marie Curie action

The project concerns application of voltage-driven reversible electrochemistry (surface chemistry and ion-exchange) to control magnetism. The research involves nanomagnetism, material science and electrochemistry. Please apply via the linked EURAXESS website.

EURAXESS project description
Master Thesis: Battery Research and Hydrogen Storage Materials

Work on developing a new electrolyte suitable for cycling Li-ion batteries at high temperature.

Job details

Physicist / Chemist / Materials scientist (f/m/d)

Category

Academics / Scientists / Engineers (master´s degree) (f/m/d)

Job description

You will develop a generic concept for sample transfer for different analytical methods including global and local reference markers for spatial inter-method correlation. Furthermore, you are responsible for the development of a concept for data and information management to fulfil the FAIR principles in correlative characterisation as well as for the categorisation of samples and characterisation methods and describe them with the help of an ontology. The publication of scientific results is also part of your responsibilities.

Personal qualification

You have a university degree (Diplom (Uni)/Master) in physics, chemistry or materials science with a completed doctorate and have already gained experience in data management as well as data processing in the field of microscopy and spectroscopy. In addition, good knowledge of physics and several years of practical experience in the field of microscopy and spectroscopy for solid state analysis, especially in the field of electron microscopy, CT and surface techniques are required. You also have analytical skills for solving physical and technical problems, basic knowledge of materials science and are interested in computer science and chemical process engineering. A strong ability to work in a team and very good written and spoken German and English skills round off your profile.

Salary

Salary category 13, depending on the fulfillment of professional and personal requirements.

 

More details Apply

Academic Employee (f/m/d) in the area of machine learning for materials science and chemistry

Category

Academics / Scientists / Engineers (master´s degree) (f/m/d)

Job description

Your responsibilities involve the initialization of collaborations within the German-Canadian Materials Acceleration Center (GC-MAC) project. This includes independent planning and implementation of research projects in the area of artificial intelligence and machine learning applied to materials science, especially for energy materials. Research areas relevant to the project are regression models (e.g. graph neural networks) for materials property prediction, generative models for inverse material design, machine learning based material simulations, probabilistic models for autonomous experiments and similar areas. The application includes among others materials for hydrogen and CO2 electrocatalysis, membrane materials as well as battery materials. In addition to your scientific tasks, you will be actively involved in the GC-MAC project. This includes planning and implementatin as well as participation in (international) project meetings, tutorials and workshops.

Personal qualification

You have a university degree in the field of materials science, physics, chemistry or computer science with a completed PhD and experience in the field of (energy) materials, materials simulations and machine learning methods, which you can demonstrate through relevant publications. Independent and creative work, strong collaboration and communication skills and a strong interest in interdisciplinary work are desired.

Salary

Salary category 13, depending on the fulfillment of professional and personal requirements.

 

More details Apply