先天-适应性免疫相互作用在癌症演进中的作用博士研究员
Fully-funded PhD studentship: Innate-adaptive immune interactions in cancer evolution
原帖优先：申请材料、截止时间与资格以原帖和学校官方说明为准。
AI 中文速览
- 研究内容
- 本项目旨在研究先天性免疫细胞（如组织驻留的2群先天淋巴细胞ILC2等）与适应性免疫细胞在癌症演进及早期肿瘤发生过程中的动态相互作用，利用小鼠模型和人类组织处理流程，结合前沿免疫学方法（高参数流式细胞术、多重成像、单细胞与空间转录组学等）揭示免疫调节机制，以设计阻断或延缓肿瘤进展的干预措施。
- 申请条件
- 要求具备细胞生物学/免疫学实验室经验（如流式细胞术、免疫荧光显微镜、细胞培养等）、分子生物学实验室经验、计算生物学数据分析经验或小鼠/人体组织工作经验；具备癌症生物学、免疫学背景，对生物信息学和计算生物学有培训需求和兴趣。
- 待遇
- 全额资助的博士生奖学金（Fully-funded PhD studentship）。课程开始日期为2027年10月1日。
- 申请方式
- 请通过剑桥大学申请者门户网站（University Applicant Portal）在线申请，选择于2027年10月开始学习；申请时请注明参考编号SW51021。
由 gemini-2.5-flash-lite 生成，博士岗判定置信度 100%。
岗位信息
- 截止
- 原帖未给出
- 学科
- 免疫与微生物学
- 合同类型
- 奖学金
- 本站收录
- 内容更新
- 导师
- Dr Tim Halim
- 来源
- The Chancellor, Masters, and Scholars of the University of Cambridge 官方招聘 · 最近核对 2026-10-10
- 详情核验
判定依据（原文摘录）
- 这是一个博士生培养机会
Fully-funded PhD studentship: Innate-adaptive immune interactions in cancer evolution
- 导师为 Dr Tim Halim
Supervisor: Dr Tim Halim
- 申请截止日期为2026年10月16日
Deadline for application: 16th October 2026
原文
Supervisor: Dr Tim Halim
Department/location: Cancer Research UK Cambridge Institute
Deadline for application: 16th October 2026
Course start date: 1st October 2027
Project details
For further information about the research group, please visit our website at https://www.cruk.cam.ac.uk/research-groups/halim-group/
The immune system is capable of detecting cancer, which forms the basis of immunotherapy. While immunotherapy has revolutionised cancer treatment in recent years, it remains unclear how exactly the immue system detects and responds to pre-cancereous lesions. Nevertheless, it is known that the activatin (or deactivation) of anti-cancer immune cells involves many different cell-types that communicate dynamically in specific tissue niches.
Our laboratory has an interest in resolving the interactions between tissue-resident immune cells, with the overall goal of identifying key mechanisms that can be targeted therapeutically at different stages of cancer. We found that recently discovered, tissue-resident, group 2 innate lymphoid cells (ILC2) can play key roles in coordinating different types of immune and non-immune cells that play critical roles in tumourigenesis (i.e. Tregs, Dendritic Cells, cancer associated fibroblasts, etc.). The project will start by asking if ILC2, or other tissue-resident innate immune cells, play an important role during tumour evolution.
The PhD project will build on ongoing work in different cancer types (pancreatic, breast, ovarian and lung), where we have already developed mouse models and human tissue processing pipelines. The candidate will learn and use cutting edge immunological methods (high parameter flow cytometry, multiplex imaging, single cell and spatial transcriptomics) in conjuction with intravital imaging and proximity labelling tools to define the dynamic interaction of immune cells in cancer. The candidate will need to master both complex 'wet lab' techniques, as well as learn how to perform robust in silico analysis of data (training will be provided by senior lab members, collaborators, or experts in the Institute core facilities). The candidate will generate hypotheses from these large descriptive datasets, which will then be tested rigorously using in vitro assays, in vivo, and ultimately in patient derived material. The overall ambition is to uncover novel mechanistic insights about immune regulation in early cancer, and to design interventions that halt or delay tumour progression.
References/further reading
Yip T et al. Science 2026 (DOI: 10.1126/science.aea5113)
Stockis J et al. Science Immunology 2024 (DOI: 10.1126/sciimmunol.adl1903)
Schuijs MJ et al. Nature Immunology 2020 ( https://doi.org/10.1038/s41590-020-0745-y )
Preferred skills/knowledge
Cell biology / Immunology laboratory experience, such as: Flow cytometry and FACS, immunofluorescence microscopy/imaging, cell culture, tumour cell killing assays, tissue processing, etc.
Molecular biology laboratory experience, such as: DNA/RNA extraction, PCR, cloning, virus production, ELISA, etc.
Computational biology laboratory experience, such as: bulk- singl cell- or spatial-transcriptomic data analysis, spatial biology analysis using HALO, Imaris, etc.
Murine or human tissue work, such as: tissue processing, tumour or immune-related in vivo models, surgical skills, transgenic animal models, UK PIL training, etc.
Knowledge: background in cancer biology, immunology, cell biology, etc. Training and interest in bioinformatics, computational biology.
How to apply
Please apply via the University Applicant Portal at: https://www.postgraduate.study.cam.ac.uk/courses/directory/cvcrpdmsc
You should select to commence study in October 2027.
References
We would appreciate it if you could ask your referees to submit their references as soon as possible upon request, despite the longer University deadline for references. They will receive a request once you have completed the References section of your application.
Please quote reference SW51021 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.