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Field
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computational simulations and related fields Theoretical knowledge of Molecular Dynamics and free energy calculations Some years of work experience in simulations with proteins/membranes and their analysis
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simulations using DFT (particularly of surface processes); kinetic Monte Carlo simulations; molecular dynamics simulations; classical and machine-learned force fields. Highly developed skills in scientific
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). Hands-on experience with computational materials methods (e.g., DFT, molecular dynamics, phase-field simulations). Proficiency in Python, TensorFlow/PyTorch, and scientific computing. Experience in
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profile: Must-have: PhD in computational simulations and related fields Theoretical knowledge of Molecular Dynamics and free energy calculations Some years of work experience in simulations with proteins
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& design, catalyst design & modelling, and carbon capturing & conversion. Proficiency in fluidized reactor design & optimization, hydrodynamics & molecular dynamics modelling (openFOAM, Ansys Fluent, LAMMPS
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requirement Experience with data analysis and machine learning models is an advantage Experience from molecular modelling or molecular dynamics simulations is an advantage Applicants must be able to work
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is an advantage Experience from molecular modelling or molecular dynamics simulations is an advantage Applicants must be able to work independently and in a structured manner and demonstrate good
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: Quantum simulation with Rydberg atom arrays (theory) Research Area: Atomic, molecular, and optical physics (AMO), quantum control, quantum simulation Relevant Fields: Quantum information science, quantum
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: Quantum Simulation with Rydberg Atom Arrays (Experiment) Research Area: Atomic, molecular, and optical physics (AMO), quantum control, quantum simulation Relevant Fields: Quantum information science
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oral communication skills. Proficiency in experimental techniques such as microscopy, microfluidics, or rheology OR molecular dynamics simulation or agent-based simulation. Competent in soft skills e.g