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Monash/Bayreuth Double PhD Degree Opportunity - Accelerating organic semiconductor discovery with generative AI, molecular dynamics and DFT Job No.: 698040 Location: Clayton (home) and Bayreuth
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 2 months ago
and storage. Your tasks # Performing DFT, MD, Wannier, Phonon calculations # Collaborating with peers including experimental project partners # Publishing results in academic and peer-reviewed journals
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functional theory (DFT) calculations of NMR parameters, powder X-ray diffraction, and other complementary analytical techniques. The postdoctoral researcher will be responsible for planning and conducting
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systems”, project number PN-IV-PCB-RO-MD-2024-0515.. The Experienced Researcher will carry out advanced theoretical DFT calculations and scientific research activities within the REDOXCOB project
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Responsibilities Theory Quantum transport modeling using NEGF; first-principles materials and interface calculations using DFT (VASP, Quantum ESPRESSO, or equivalent). Atomistic spin dynamics
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that also integrates theoretical aspects beyond spectroscopic observables. Field of Work - Quantum chemical calculations (using mainly DFT) and hybrid QM/MM calculations - Classical, ab
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on 2D materials and nanomaterials. Theoretical design of materials (DFT calculations). Calculation of the magnetic properties of the studied systems. Characterization of nanostructures and 2D materials
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(DFT) simulations and develop machine learning potentials to investigate zeolite-related systems. The role will focus on delivering research projects and promoting research excellence in this area. The
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interdisciplinary teams. • For experimental applicants: hands-on experience with synthesis and characterization equipment. • For theory/AI applicants: experience with DFT, MD, MLIPs, or AI/ML frameworks.
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position within a Research Infrastructure? No Offer Description Activities and context: The fellow will develop machine-learning interatomic potentials (MLPs), trained on density functional theory-DFT data