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be tasked with investigating the molecular mechanisms of endoplasmic reticulum-mediated protein quality control using Arabidopsis thaliana as a convenient genetic model system. Requirements
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Mathematics, particularly in research areas such as Applied Analysis/Computational Mathematics/Mathematical Modeling/Probability and Statistics, along with excellent professional and research experience; and 3
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plasticity with a focus on cancer stemness using hepatocellular carcinoma as a model system, that is part of a collaborative project. For further information, please contact Professor Stephanie Ma at stefma
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Stephanie Ma on research projects relating to cancer cell plasticity with a focus on cancer stemness using hepatocellular carcinoma as a model system, that is part of a collaborative project. For further
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possess extensive experience in developing deep learning algorithms Excellent programming skills (e.g., proficiency in Python, PyTorch, OpenCV) and experience in deep learning model optimization and
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Post-doctoral Fellow in the Department of Orthopaedics and Traumatology, School of Clinical Medicine
) to model orthopedic pathologies. Manage and perform functional studies using animal models (e.g., transgenic mice) to evaluate disease progression and therapeutic efficacy. Utilize induced pluripotent stem
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funding availability and satisfactory performance. Applicants should possess a Ph.D. degree with a specialisation in Psychology and Computational Modelling/advanced neuroimaging data processing skills/big
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Computational Modelling/advanced neuroimaging data processing skills/big data processing techniques. They should have a strong interest in experimental research and demonstrated scientific expertise and excellent
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. They will also be responsible for developing and integrating electronic circuits, camera modules, various sensors, and embedded control systems. Responsibilities include relevant modeling, simulation, and
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, transcriptomics data, Nanopore long read sequencing analysis and/or multimodality deep learning model development in different sarcomas. Publications in related fields will be a strong advantage. Opportunities for