Research Associate – Device characterization of tandem solar cells and machine learning

Predictive Model For Tandem Cell Stability

You will be a member of a consortium of leading research institutes and an industry partner. Your task is to build up a predictive model for tandem cell stability.

Responsibilities

• Receive tandem solar cells from a partner institute and perform high‑throughput degradation and characterization.
• Develop existing predictive models with respect to the prediction of time‑series data in hybrid AI workflows, considering physical model parameters.
• Adapt the protocol of the high‑throughput characterization to maximize the predictive capacity of the AI model.
• Scientific communication of the results (publications, conference presentations).
• Intense interaction with the consortium.

Qualifications

• Master and PhD degree in materials science, physics, chemistry, informatics, machine learning, energy technology or related subjects.
• Prior experience in building predictive models using regression techniques, neural networks (CNN, GNN) or symbolic regression.
• Experience in the dissemination of scientific results, demonstrated by publications and presentations at conferences.
• Willingness and ability to participate in international meetings.
• Experience with conducting and documenting scientific experiments as well as processing and analyzing data (Python, Origin).
• Good communication in English; knowledge of German advantageous (but not compulsory).

Offer

• Varied and diverse role in an international environment.
• Work‑life balance: flexible working location after consultation and in line with upcoming tasks and on‑site appointments.
• 30 days of vacation plus additional days off.
• Flexible working time models, including options close to full‑time.
• Professional development with targeted, individual support.
• Fair remuneration: classified in pay grade 13 of the TVöD‑Bund.
• Annual bonus and capital‑forming benefits.
• Fixed‑term position limited to 2 years.

We welcome applications from people with diverse backgrounds, including age, gender, disability, sexual orientation/identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities is important to us.