Zveřejněno před 7 dny
Intern
Hiring entity: Shell GSI BV
- Způsob práce neuveden
- Plný úvazek
- Stáž
Popis nabídky
, Netherlands
Worker Type:
Interns (Fixed Term) (Trainee)
Posting Start Date:
November 7, 2026
Job Description:
DESCRIPTION OF INTERN ASSIGNMENT
Intern assignment
Describe the responsibilities and activities related to the Assignment. If relevant, relate these activities to the requirements for completion of the Internship as set by the Institute of Education. Include details of department where the Internship will be carried out.
6-months MSC project internship based at ETCA
Title : Towards the Next Generation of Hybrid Second Order Group Contribution Frameworks for the Prediction of the Melting Point and Viscosity of Heavy and Branched Alkanes
Goals and objectives
Accurate prediction of melting point and viscosity remains challenging for heavy and highly branched alkanes due to the strong influence of molecular architecture, conformational flexibility, and intermolecular interactions. To address this need, a next-generation of Group Contribution framework for predicting the melting point and viscosity of heavy and branched alkanes may be formulated by augmenting classical first- and second-order structural groups with DFT-derived molecular descriptors and machine-learning corrections. The GC component captures the contribution of molecular fragments and branching patterns, while DFT quantifies electronic and conformational features governing intermolecular forces, crystal lattice stability, and liquid flow behavior. Machine learning algorithms are then used to learn higher-order interactions between structural groups and quantum-mechanical descriptors, providing correction terms to the classical GC predictions. Such a DFT-ML-GC hybrid methodology retains the simplicity, interpretability, transferability and extrapolation capability of second order group contribution approaches while significantly enhancing prediction accuracy for complex hydrocarbon systems beyond the range of available experimental measurements.
Deliverable:
MSc thesis and final presentation
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