The hired post doctoral researcher will work in an interdisciplinary consortium project between computational physicists and computer scientists at the Nanoscience Center and in the Faculty of Information Technology of University of Jyväskylä, Finland. The project aims at new breakthroughs in the area of computational research of nanomaterials, specifically developing new open source algorithms and software based on artificial intelligence (AI), for reliable structural predictions of ambiently stable hybrid metal nanoparticles in the size range up to a few nanometers in diameter and analyzing correlations in the existing experimental and computational nanoparticles' structure-property data. Hybrid metal nanoparticles, consisting of up to a few hundred metal atoms and more than one hundred organic capping molecules, are expected to have applications in biolabeling, catalysis, medicine, and solar energy. By the help of new AI-based software developed in this project, which will combine intelligent memetic algorithms using local and global search with multi-objective optimization procedures, incomplete experimental structural information on nanoparticles can be effectively utilized for computational structural models whose validity and merits will be evaluated against
 complementary experimental information of nanoparticles' measured properties. The improved understanding of nanoparticles' structure-property relationships and of the initial structures that dominate their nucleation mechanisms in solution helps to design more stable, functional nanoparticles for various applications. The generated new software can be used in other areas of nanomaterials research (such as conducting nanowires, catalytically active metal nanoparticles, new metal-organic framework materials) for improved structure prediction and structure-property research. The consortium has a broad and strong network of international collaborations in the communities of nanoparticle research and computer science, offering the hired researcher ample opportunities to develop his/her knowledge in these areas. A successful candidate for this position should have a PhD degree in physics or physical chemistry with specialty in computational condensed matter physics, materials science or quantum chemistry. Good programming skills and knowledge of machine learning methods are regarded as advantage. The position is available August 1, 2018. The deadline for applications is April 30, 2018.  For more information, please contact Academy Professor Hannu Häkkinen (hannu.j.hakkinen (at) jyu.fi).  To access the web application form, click this link:

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