99 molecular-modeling-or-molecular-dynamic-simulation Postdoctoral positions in Netherlands
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- University of Groningen
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- Leiden University; 's-Gravenhage
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- Maastricht University (UM); Maastricht
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- Radboud University Medical Center (Radboudumc)
- Radboud University Medical Center (Radboudumc); Nijmegen
- Radboud University; Nijmegen
- The Netherlands Cancer Institute
- The Netherlands Cancer Institute; Amsterdam
- Tilburg University
- Tilburg University; Tilburg
- University of Groningen; Groningen
- Vrije Universiteit Amsterdam (VU)
- Vrije Universiteit Amsterdam (VU); Amsterdam
- Wageningen University & Research
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and their potential applications in a dynamic environment with a collaborative, multi-disciplinary team. You will be the backbone of the project, supporting the activities of your team. In this role
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assembly, recognition, transport, motion, and catalysis. The goal is to create new structures and functions, with an emphasis on molecular switches and motors, dynamic molecular systems, responsive materials
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complex (NPC), responsible for all molecular transport in and out of the cell nucleus. These pores exhibit an intriguing selectivity where most proteins are blocked from transport, while particular
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in systems engineering, industrial engineering, operations research, supply chain management, or a related field. Experience with system modeling or scenario analysis (e.g., system dynamics, agent
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profitability. Examples include optimizing production speeds to balance output, equipment deterioration, and energy consumption in manufacturing, or designing dynamic pricing and allocation policies in rental
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of developing cutting-edge deep learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In
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. The DELPHI project, a collaboration between UMCG, UG, Health-Ecore and Protyton, aims to advance lung cancer treatment using molecular modeling and computational analysis for personalised care. DELPHI seeks
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applications from individuals with experience in: Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation techniques
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unexpected alternative strategy: by lining membrane pores with intrinsically disordered proteins (IDPs) to guard the gap. The best example is the nuclear pore complex (NPC), responsible for all molecular
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and proven affinity with sustainability and teaching will also be considered. Experience with prospective life cycle assessment and/or material flow analysis/dynamics stock flow modelling. Basic