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Postdoc (M/F) :Development of machine learning m ... (No replies)
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Missions
The postdoctoral project will focus on the development and application of ab initio multireference methods assisted by machine learning models for the exploration of multi-state potential energy surfaces of polyatomic molecules and the associated nonadiabatic dynamics.
Activities
- Development of theoretical models
- Implementation of theoretical models
- Application of the methods developed;
- Valorization of results (writing of articles and scientific reports, oral presentations).
- Participation to the laboratory activities.
Skills
- Solid background in theoretical chemistry
- Experience in the calculation of excited states and particularly in the field of computational photochemistry. The good knowledge of multireference methods (CASSCF / CASPT2 / NEVPT2) will be considered as an added value.
- A very good knowledge of computer systems based on Linux / Unix and programming languages (python, fortran, C ++) is desirable.
- Excellent communication in English.
Contract Period : 12+12 months
Expected date of employment :June/July 2020
Proportion of work : Full time
Remuneration : 2643 € à 3766 € according to candidate's experience
Desired level of education : PhD
Experience required : PhD in theoretical/computation chemistry or material science
Work Context
The Laboratoire de Physique et Chemie Théoriques (LPCT; UMR CNRS 7019) of the University of Lorraine is an internationally recognized research unit which conducts research in the following five scientific areas:
1) Dynamics and Symmetries;
2) Radiation-Matter Interaction;
3) Liquid state, Interfaces and Solvation;
4) Solid state: Structure and Properties;
5) Biophysics and Biochemistry;
The laboratory currently brings together the majority of theorists (physicists or chemists) from Lorraine.
Interested candidate should send an email with cv, letter of motivation and references to [email protected]