Senior Research Position At Imdea Energía To Lead A New In Silico Unit

Description

IMDEA Energy is opening a Senior Researcher Position to establish and lead a new In Silico Unit devoted to predictive multiscale computational science for sustainable energy materials, with strong institutional support and close interaction with world-class experimental researchers.

The candidate will be responsible for defining the scientific and technological roadmap of the In Silico Unit, selecting the main lines of research, participating in and leading national and international R&D projects, coordinating multidisciplinary teams and representing the institute in scientific, technological, industrial and regulatory bodies in the field of multiscale modeling applied to materials and energy.

• Define and implement the scientific vision and technological strategy of the In Silico Unit, establishing an internationally recognized research program in predictive computational science for sustainable energy materials.
• Develop innovative multiscale computational methodologies to understand, predict and optimize the behavior of materials and processes relevant to the energy transition.
• Advance predictive modelling frameworks by integrating physics-based approaches with modern computational tools, including data-driven methodologies where appropriate.
• Foster close collaboration with IMDEA Energy's experimental research groups to accelerate the discovery, validation and optimization of materials and energy technologies.
• Build, lead and mentor a multidisciplinary research team, promoting scientific excellence, independence and talent development.
• Lead and participate in competitive European, National and Regional R&D projects, as well as industrial research and technology transfer activities.
• Establish strategic collaborations with leading universities, research centers, technology platforms, and industrial stakeholders.
• Promote scientific excellence through high-impact publications, invited lectures, international conferences, software developments, patents and other research outputs.
• Contribute actively to positioning IMDEA Energy as an international reference in computational materials science for sustainable energy technologies.

• PhD in Materials Science, Chemistry, Physics, Chemical Engineering, Computational Science, Applied Mathematics, or closely related disciplines.
• At least 8 years of postdoctoral research experience in computational materials science, multiscale modeling, or related fields.
• Demonstrated international scientific excellence in computational modeling applied to materials for energy technologies, demonstrated through high-impact scientific publications and scientific leadership.
• Proven ability to define and lead an independent research program, including successful coordination of competitive national and/or international research projects.
• Demonstrated experience in scientific leadership, team building and supervision of researchers at different career stages.
• Strong commitment to interdisciplinary research and collaboration with experimental scientists.
• Required documents
• PhD Certificate
• Motivation Letter
• Research Vision Statement including expected research lines and integration within the institute (2 pages maximum) (brief research proposal)

• Expertise in one or more computational modeling approaches across different length and time scales, including atomistic, molecular, mesoscale or continuum modelling.
• Experience developing predictive computational methodologies for understanding structure–property–performance relationships in materials.
• Experience in computational materials design, particularly in areas relevant to sustainable energy technologies such as adsorption, catalysis, electrochemical systems or related fields.
• Experience integrating computational modelling with experimental research.
• Experience incorporating modern computational tools, such as data-driven methods, machine learning, surrogate models or uncertainty quantification, to enhance predictive modelling.
• Experience using High Performance Computing (HPC) infrastructures and large-scale scientific computing.
• Proficiency in scientific programming and the…