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Tom Andersson

Research Team Leader

VTT Technical Research Centre of Finland

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Finland

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Research Interests

Artificial Intelligence

10%

Density Functional Theory

10%

Chemistry

10%

Computational Materials

10%

Physics

10%

Machine Learning

10%

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Positions1

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VTT Technical Research Centre of Finland

VTT Technical Research Centre of Finland

PhD and Postdoctoral Positions in Battery Materials and Materials Acceleration Platform at VTT

VTT Technical Research Centre of Finland is seeking motivated candidates for PhD and Postdoctoral Researcher positions in the field of next-generation battery materials, with a focus on the development of a Materials Acceleration Platform (MAP) for novel battery chemistries. This opportunity is ideal for those passionate about energy storage, computational materials science, and machine learning applications in material design. The research will be conducted within VTT's integrated computational materials engineering team, contributing to the Knowledge Driven Design research area. The MAP leverages advanced automation, high-quality characterization, data generation, integrated computational materials engineering (ICME), quantum computing, and data-driven methods such as analytics and artificial intelligence to accelerate the discovery and predictive synthesis of battery cathode materials. The team also develops VTT ProperTune, an ICME concept for multiscale modeling to optimize computational material design and reduce reliance on physical testing. PhD candidates will join VTT's dynamic PhD Programme, which supports goal-oriented doctoral research aligned with VTT’s strategic priorities and offers collaboration with Finnish universities. Postdoctoral researchers will benefit from VTT's Postdoc programme, designed to support scientific excellence and career development in applied research and industry collaboration. Both roles offer the chance to work in a world-class research environment, collaborate with top experts, and contribute to impactful innovations in energy storage and materials science. Key research activities include training and applying machine learned interatomic potentials, developing computational chemistry software, calculating electronic structures using density functional theory and tight binding methods, and disseminating research through publications and conferences. Candidates will also have opportunities to supervise junior team members and participate in interdisciplinary projects. Applicants should have a strong background in material science, density functional theory, and machine learning. Fluency in English is required, and Finnish skills are advantageous. The PhD position is open to those seeking to complete a doctoral degree in a relevant field, while the postdoctoral position requires a recent PhD (within the last five years). Successful candidates will be curious, ambitious, collaborative, and eager to learn. VTT offers a supportive research community, state-of-the-art facilities, and a comprehensive benefits package, including six weeks of paid holidays after one year, exercise and culture benefits, and well-being services. The positions are based in Espoo, Finland, and are full-time, fixed-term contracts (PhD: 4 years; Postdoc: 2 years with possible extension). To apply, submit your CV and application with your salary request via the VTT recruitment system. Applications are reviewed on a rolling basis, and the position may be filled before the deadline of January 11, 2026. For further information, contact Research Team Leader Tom Andersson at [email protected]. Keywords: battery materials, materials acceleration platform, machine learning, computational materials science, density functional theory, cathode materials, physics, material science, engineering, artificial intelligence.

1 month ago