01
招聘信息
We are seeking a Postdoctoral Research Fellow for a (up-to) 3-year position to work on an exciting project funded by the Medical Research Council (MRC) UKRI and led by Dr Bingxin Lu at the University of Surrey, UK (Deadline 30 April 2025).
02
招聘方向
The project aims to reconstruct the evolutionary dynamics of chromosomal instability in cancer genomes. Understanding how chromosomal instability evolves during the progression from precancerous lesions to malignancy, metastasis, and treatment resistance is important for cancer detection and treatment. Building upon our previously published method, CNETML (https://doi.org/10.1186/s13059-023-02983-0), this project will develop more realistic evolutionary models of copy number alterations and better phylogenetic inference methods with wider applicability. The developed methods will then be applied to extensive publicly available datasets to investigate the dynamics of chromosomal instability. Our new methods will enhance the toolkit for cancer researchers and drive broader applications of cancer phylogenetic inference. The insights gained from the inferences will also support personalized therapy and advance public health efforts.
The successful candidate will not only design and conduct the research but also write and communicate results as scientific papers and in scientific presentations at national and international conferences.
欢迎对下列方向感兴趣的同学申请：计算生物，系统进化树，贝叶斯统计，癌症演化，染色体不稳定性，基因组数据分析。
如果确定录用，可以提供资助申请英国签证，包括UK Global Talent Visa。
03
导师简介
Dr Bingxin Lu is currently a Surrey Future Fellow, at the Section of Systems Biology and Surrey Institute for People-Centred AI, University of Surrey. She has recently been awarded a three-year MRC new investigator grant, which supports this Postdoc position. Before joining Surrey, she was a Postdoc at University College London, working on dynamical modelling of chromosomal instability (CIN) in cancer genomes. Previously, she was a Postdoctoral Fellow at Genome Institute of Singapore, where she mainly developed pipelines and methods to analyse tumour heterogeneity and clonal evolution in liver and lung cancer genomes. She completed her PhD in Computational Biology at School of Computing National University of Singapore, where she developed machine learning and phylogenetic methods for problems related to lateral gene transfer. She obtained her Master’s and Bachelor’s degree from Software Engineering Institute East China Normal University, where she led the development of platforms for high-throughput biological data analysis, including RNA-Seq and proteomic data. Her research is in the broad field of computational biology, which bridges software engineering, machine learning, algorithms, statistics, phylogenetics, population genetics, and omics. She has developed several new methods and applied available methods to tackle basic questions arising in the study of species and cancer evolution. Her current primary interests are evolutionary dynamics of cancer genomes, especially those driven by CIN, which are still less well studied than point mutations but critical in tumorigenesis and patient treatment.
导师主页
https://icelu.github.io/
04
招聘要求
The successful candidate will have a strong research background and should have a PhD (or close to completion) in computational biology, bioinformatics, computer science, or related fields that include a substantial amount of computing and mathematical/statistical modelling, ideally related to phylogenetic method development. Working knowledge in genomics, evolutionary biology, cancer biology, or population genetics is desirable. Experience in programming is essential.
Qualifications, experience and knowledge
PhD (or close to completion) in computational biology, bioinformatics, computer science, or related fields that include a substantial amount of computing and mathematical/statistical modeling, ideally related to phylogenetic method development (essential)
A strong record of publications in international, peer-reviewed journals (desirable)
Working knowledge in genomics, evolutionary biology, cancer biology, or population genetics (desirable)
An undergraduate degree in computer science, mathematics, statistics, physics, engineering, or another quantitative discipline (desirable)
Skills and abilities
Proficiency with Unix-based systems and programming, ideally in multiple languages, including but not limited to C++/C, Python, and R (essential)
Solid mathematical and statistical modeling skills, ideally in Markov models and Bayesian statistics (essential)
Excellent English and communication skills (essential)
Experience in designing and implementing algorithms, ideally related to optimization and Markov chain Monte Carlo (MCMC) techniques (essential)
Experience in developing and deploying software in academic or industry settings (desirable)
Experience in high-throughput sequencing data analysis, ideally using compute clusters or cloud computing (desirable)
Personal attributes
Strong commitment to rigorous and high-quality reproducible research (essential)
Highly motivated, curious, and enthusiastic in research (essential)
Openness to learn new techniques in a fast-moving interdisciplinary field (essential)
Ability to work both independently and collaboratively while maintaining integrity and accountability (essential)
Ability to work harmoniously with colleagues and students from diverse cultures and backgrounds (essential)
05
申请方式
Please submit your cover letter, CV, and contact of three references with your application on the University of Surrey Website (http://jobs.surrey.ac.uk/017125).
For informal inquiries, please contact Dr Bingxin Lu b.lu@surrey.ac.uk.
06
大学简介
The University of Surrey is a global community of ideas and people, dedicated to life-changing education and research.
We are ambitious and have a bold vision of what we want to achieve – shaping ourselves into one of the best universities in the world, which we are achieving through the talents and endeavour of every employee.
Our culture empowers people to achieve this aim and to collectively, and individually, make a real difference.
The University of Surrey is committed to providing an inclusive environment that offers equal opportunities for all. We value everyone in our community and are seeking to increase the diversity. Therefore, we particularly encourage applications from under-represented groups, such as people from Black, Asian and minority ethnic groups and people with disabilities.
萨里大学坐落于充满活力和历史悠久的吉尔福德，位于英格兰东南部中心，距离伦敦市中心仅34分钟火车车程。学校所在地吉尔福德位于萨里郡，是一座充满活力，文化和历史的城市，被“星期日泰晤士报”评为2014年全英最佳居住地之一。Stag Hill 主校区距离市中心仅10分钟的步行路程 ，这里是一处令人着迷，优渥的，适宜学习和生活的地方 (https://www.surreyuniversity.cn/)。
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