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PhD position in liquid-vapor interactions (No replies)
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A PhD fellowship in Computational Mineral Physics is now open at the Institut de Physique du Globe de Paris, within the ab initio group led by Dr. Razvan Caracas.
The research will focus on the chemical interactions between atmospheres and magmas.
The successful candidate will leverage ab initio and machine learning molecular dynamics simulations to compute the solubility of volatiles in molten silicate. These advanced simulations, which offer an accurate depiction of the system's physics independent of specific experimental input, are key to understanding the thermodynamic, thermochemical, and vibrational properties of the melt and mixtures, as well as extracting chemical speciation and transport properties.
The PhD student will also have the opportunity to participate in experimental work at the University of Chicago's facilities within the group of Prof. Andrew Campbell, providing a holistic experience combining both theoretical and practical aspects of research.
The end goal of this project is to integrate the findings from atomistic simulations and solubility experiments to develop improved models for the interiors of exoplanets, providing fresh insights into the complex dynamics of our universe.
The PhD fellow will join the ab initio group under the leadership of Dr. Razvan Caracas, working alongside a dedicated team of computational mineral physicists at the IPGP. As part of the fellowship, the successful candidate will fully integrate into the vibrant academic life of the IPGP, participating in regular PhD courses and activities. This position offers a unique opportunity to work at the forefront of computational mineral physics, contributing to our understanding of planetary science and beyond. We encourage all qualified and interested candidates to apply.
The ideal candidate for the PhD position in computational mineral physics, focusing on ab initio simulations, should have a strong academic background in physics, chemistry, materials science, or a related field. Proficiency in programming languages, such as Python, is required due to the computational nature of the research. Prior experience with numerical methods and high-performance computing is highly desirable. Familiarity with molecular dynamics simulations, especially ab initio methods, would be advantageous. Additionally, the candidate should have strong analytical skills, be capable of independent and creative thinking, and have a solid understanding of thermodynamics and statistical mechanics. Excellent written and oral communication skills in English are necessary for presenting research findings and collaborating within an international team. Lastly, a master's degree in a relevant field is typically required for entry into a PhD program.
The position will start in October 2023.
Questions may be addressed to Drs. Razvan Caracas ([email protected]). To apply, please follow the link to the CNRS employment website:
https://emploi.cnrs.fr/Offres/Doctorant/UMR7154-RAZCAR-001/Default.aspx?lang=EN