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西交利物浦大学三校联合培养博士项目招生/宋鹏飞博士课题组
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Project Title项目课题 基于液滴微流控的鼻咽癌生物标志物超灵敏检测 Droplet microfluidics for ultrasensitive biomarker nasopharyngeal carcinoma detection Project Code 项目编号 SFXJTU2618 Brief introduction of the three supervisors (e.g. key academic background, work experience, research area, etc.) 三校导师简介，包括但不限于学术背景、工作经历及研究领域等 南浪 研究员 南浪研究员主要从事自动化液滴微流控与高精度生化检测研究，重点关注多物理场流体操控、高通量液滴系统及单细胞精准操纵技术。近五年以第一作者在 Nature Biomedical Engineering、Science Advances、Small 等期刊发表论文13篇，并申请多项国际及国内专利。其研究为高灵敏生化分析、单细胞检测及传染性疾病检测提供了重要技术基础。 宋鹏飞 博士 宋鹏飞博士现任西交利物浦大学高级副教授、博士生导师，2018年获加拿大麦吉尔大学博士学位。其研究主要聚焦微纳传感、微流控系统及自动化检测技术，并推动人工智能与自动化在生物医学检测中的应用。近五年发表SCI论文60余篇，主持和参与国家自然科学基金等科研项目20余项，并担任 IEEE Robotics and Automation Letters 副主编。 Simon Maher 教授 Simon Maher教授主要从事质谱、分析仪器与先进传感技术研究，重点关注小型化、便携式和自动化分析系统的开发。他在质谱、离子迁移谱、SERS、侧向层析、化学传感及微流控等领域具有丰富经验，并擅长仪器设计、系统集成、自动化及数据分析。相关技术广泛应用于临床诊断、食品检测、环境监测和生化分析等领域。 Eng Gee Lim 教授 Lim教授研究涵盖人工智能、机器人、智能医疗、无线通信及AI+应用等领域，在科研管理和产学合作方面具有丰富经验。迄今主持和参与大量科研与产业项目，累计科研经费超过7000万元，并发表或获得约400项论文、专利及专著。 English Profiles Dr. Nan Lang Dr. Nan Lang focuses on automated droplet microfluidics and high-precision biochemical analysis, with expertise in multiphysics fluid manipulation, high-throughput droplet systems, and precise single-cell manipulation. He has published 13 first-author papers in leading journals including Nature Biomedical Engineering, Science Advances, and Small, and has filed multiple international and domestic patents. His work supports ultrasensitive biochemical sensing, single-cell analysis, and infectious disease detection. Dr. Pengfei Song Dr. Pengfei Song is a Senior Associate Professor and PhD Supervisor at Xi’an Jiaotong-Liverpool University. He received his PhD from McGill University in 2018. His research focuses on micro/nano sensing, microfluidic systems, and automated analytical technologies, with particular interest in AI-enabled biomedical detection. He has published over 60 SCI-indexed papers in the past five years and led or participated in more than 20 research projects. He currently serves as an Associate Editor of IEEE Robotics and Automation Letters. Professor Simon Maher Professor Simon Maher specialises in mass spectrometry, analytical instrumentation, and advanced sensing technologies, with particular emphasis on miniaturised, portable, and automated analytical systems. His expertise includes mass spectrometry, ion mobility, SERS, lateral flow assays, chemical sensing, microfluidics, instrument design, system integration, automation, and data analysis. His research has been applied to clinical diagnostics, food testing, environmental monitoring, and biochemical analysis. Professor Eng Gee Lim Professor Eng Gee Lim’s research interests include artificial intelligence, robotics, intelligent healthcare, wireless communications, and AI-enabled applications. He has extensive experience in academic leadership and industry collaboration, has secured over RMB 70 million in research funding, and has produced approximately 400 publications, patents, and monographs. Key aspect/summary of your research project项目简介 鼻咽癌（nasopharyngeal carcinoma，NPC）是一种在中国南方地区发病率尤为突出的恶性肿瘤。其临床预后与确诊时的疾病分期密切相关。然而，早期鼻咽癌通常缺乏明显症状，容易导致诊断延迟并造成不良预后。因此，亟需开发更加灵敏、可靠的诊断方法，以实现鼻咽癌的早期识别和精准病程监测。循环Epstein–Barr病毒（Epstein–Barr virus，EBV）DNA是非角化型鼻咽癌公认的生物标志物，已广泛用于疾病筛查和预后评估。目前常用的检测方法，包括定量PCR和下一代测序，主要基于样本的整体分析。这类方法在病毒载量较低时灵敏度有限，同时会掩盖病毒基因组的异质性，因此难以准确检测早期鼻咽癌，也难以深入研究具有临床意义的EBV变异。液滴微流控通过将样本分配至大量彼此独立的微反应器中，为数字化分析和单基因组分析提供了一种强有力的技术路径。该技术能够对单个病毒基因组进行独立扩增和绝对定量，从而显著提高检测灵敏度。此外，单基因组分辨率还为研究可能与疾病进展及治疗响应相关的EBV遗传异质性提供了有效手段。然而，要实现临床转化，仍需解决液滴稳定操控、高通量筛选以及可靠基因组提取等关键挑战。 因此，开发一种用于单EBV基因组分析的自动化液滴微流控平台，对于突破现有诊断方法的局限、推动鼻咽癌的早期高精度诊断与病程监测具有重要意义。 Nasopharyngeal carcinoma (NPC) is a malignancy with exceptionally high incidence in Southern China. Clinical outcome is strongly dependent on the stage at diagnosis, yet early-stage NPC is often asymptomatic, leading to delayed detection and poor prognosis. Consequently, there is an urgent need for more sensitive and reliable diagnostic approaches that enable early identification and precise disease monitoring. Circulating Epstein–Barr virus (EBV) DNA is a well-established biomarker for non-keratinizing NPC and has been widely used for screening and prognostic evaluation. Current detection methods, including quantitative PCR and next-generation sequencing, are mainly based on bulk analysis. These approaches show limited sensitivity at low viral loads and obscure viral genome heterogeneity, making it difficult to faithfully detect early-stage NPC or investigate clinically relevant EBV variants. Droplet microfluidics offers a powerful strategy for digital and single-genome analysis by partitioning samples into large numbers of isolated microreactors. This enables independent amplification and absolute quantification of single viral genomes with greatly improved sensitivity. In addition, single-genome resolution provides an effective means to study EBV genetic heterogeneity that may be associated with disease progression and treatment response. However, robust droplet manipulation, high-throughput screening, and reliable genome extraction remain key challenges for clinical translation. Therefore, developing an automated droplet-based platform for single-EBV-genome analysis is of great significance for overcoming current diagnostic limitations and advancing early, high-precision diagnosis and monitoring of NPC. Other preferred qualification and skill set of the candidate 对项目候选人的其他学术背景及技能要求 Candidates should have a background in microfluidics, biomedical, chemical, mechanical, control, electronic, or electrical engineering. Experience in molecular diagnostics, droplet generation, image analysis, system integration, or laboratory automation is desirable. Strong experimental, programming, and interdisciplinary communication skills are preferred. 候选人应具有微流控、生物医学工程、化学工程、机械工程、控制工程、电子或电气工程等相关专业背景。具有分子诊断、液滴生成、图像分析、系统集成或实验室自动化经验者优先，并应具备良好的实验、编程及跨学科沟通能力。 有意者请将个人简历及其他有助于申请的材料发送至 Pengfei.Song@xjtlu.edu.cn 注:不用跟帖，直接发邮件就行，主题请注明博士申请。 |
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2026-09-04 11:15:53, 230.73 K
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