荷兰代尔夫特理工大学 电气工程、数学与计算机科学学院 生物信息学实验室 招聘 微生物基因组学算法 博士

1. 学校简介：
   1. 学校名称：代尔夫特理工大学（TU Delft）
   2. 世界排名：2025年QS世界大学排名中位居第49
2. 项目简介：

本项目聚焦于通过计算机科学和数学技术对传染性病原体进行监测。博士生将在代尔夫特生物信息学实验室（Delft Bioinformatics Lab）与智能系统系（Intelligent Systems Department）合作，开发图算法用于微生物基因组学。研究内容包括病毒、细菌和酵母的基因组组装、变异检测及变异跟踪，帮助监控影响致病性、药物耐药性和疫苗逃逸等特征的基因突变。博士生将专注于基因组拼接、变异调用和变异追踪，分析不同菌株在混合样本中的流行变化。

3. 招生详情：
   1. 学位类型：博士
   2. 研究方向：

开发用于识别和追踪病毒、细菌和酵母中基因突变的算法。

使用图论、离散优化和机器学习等技术处理大规模基因组数据。

解决基因组变异与测序错误的区分、同源基因中的突变区分、大规模结构变异的处理等问题。

1. 薪资福利：

第一年至第四年薪资范围：€3059 - €3881，外加8%的假期津贴和8.3%的年终奖金。

4. 申请要求：
   1. 学术背景：计算机科学或相关领域的硕士学位（或同等学历）。
   2. 技能要求：

强大的计算能力，包括算法设计和数据分析。

有生物信息学、编程和软件工程的经验。

有图算法、离散优化或机器学习相关经验者优先。

良好的英语沟通能力（口语与书面）。

对学习新技能、知识交流和团队合作充满热情。

愿意教授和指导学生，推动生物信息学领域的发展。

1. 申请材料：

简历

学术成绩单（包括本科和硕士学位）

动机信（阐述为什么有兴趣攻读博士学位、为什么这个项目吸引你、你具备的相关能力，以及你希望从该职位中获得什么）

1. 提交截止日期：2025 年 11 月 30 日

5. 如何申请&更多信息：
   1. 申请链接：https://careers.tudelft.nl/job/Delft-PhD-Position-Algorithms-for-Microbial-Genomics-2628-CD/1329783657/
   2. 联系方式：导师：Dr. Jasmijn Baaijens（j.a.baaijens@tudelft.nl）
   3. 更多信息：

导师个人网站：https://jbaaijens.github.io/

实验室：https://www.tudelft.nl/index.php?id=24108

6.  

PhD Position Algorithms for Microbial Genomics 

Job description

Bacterial and viral infections pose one of the biggest threats to human health. Genomic mutations (i.e. changes to the genome sequence) can affect characteristics of the pathogen, such as virulence, drug response and vaccine escape. To monitor these mutations and to understand their impact, it is crucial to analyse genomic big data efficiently and accurately.

 

Genomes are studied through genome sequencing, but these technologies can only read DNA fragments of limited length. We enable biological interpretation of these sequencing data sets by developing algorithms based on graph theory, discrete optimization and machine learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts. For example, we would like to be able to track how the prevalences of different strains in a mixed sample change over time.

 

Your role:

You will develop and implement algorithms to find, quantify and track mutations in evolving populations of viruses, bacteria and/or yeasts. Some challenges that you will be facing are:

• How to distinguish genomic mutations from sequencing errors using the latest sequencing technologies?
• How to distinguish mutations in a given gene from mutations in homologous genes?
• How to deal with large-scale structural variation?
• How to link mutations together into genomes across distances longer than the read length?

 

You will address these challenges by formulating appropriate graph optimization problems (e.g. minimal edge covering, minimal path covering, shortest paths, clustering) and solve these problems using techniques such as linear/integer programming or by designing suitable heuristics.

 

The algorithms that you develop can play an important role in pathogen surveillance, infection treatment design, and/or understanding evolution. Depending on your expertise and interests, your projects can be more applied (in collaboration with experimental groups) or more theoretical. More information about ongoing research, publications and media can be found [here](https://jbaaijens.github.io).

 

You will be part of [the Delft Bioinformatics Lab](https://www.tudelft.nl/index.php?id=24108) in the Intelligent Systems department at TU Delft. In this project we also work together with experimental groups at TU Delft and beyond. The Delft Bioinformatics Lab has strong algorithmic and machine learning expertise, with a profound interest in new biomolecular technologies. We teach bioinformatics courses across several programs within TU Delft and nationally, in which you will also assist.

 

We value different perspectives and we strongly believe that diversity drives innovation. We offer an open and safe working environment for employees and students regardless of their nationality, cultural background, gender or sexual orientation. Anyone who meets the application criteria and whose curiosity was triggered by the description above is strongly encouraged to apply.

 

Job requirements

 

To be considered for the position you must:

• have a master’s degree (or equivalent) in Computer Science.
• have strong computational skills in algorithm design and data analysis.
• have experience with courses and projects in Bioinformatics.
• have experience with programming and/or software engineering. Strong programming skills are a definite plus.
• have good communication skills in English (both verbal and written).
• be eager to push yourself to learn new skills, exchange knowledge and collaborate where possible.
• be willing to teach and guide students.     

 

TU Delft (Delft University of Technology) 

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. 

 

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration. 

 

Challenge. Change. Impact! 

 

Faculty of Electrical Engineering, Mathematics and Computer Science 

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment. 

 

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science. 

Conditions of employment 

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

 

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3059 - €3881 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.  

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. 

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.  

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.  

 

Additional information

If you would like more information about this vacancy or the selection procedure, please contact Dr. Jasmijn Baaijens, via j.a.baaijens@tudelft.nl.

 

Application procedure

Are you interested in this vacancy? Please apply no later than 30 Nov 2025 via the application button and upload the following documents:

• CV
• Motivational letter
• Academic transcripts (both MSc and BSc degrees)

The letter of application should summarise (I) why the applicant wants to do a PhD, (II) why the project is of interest to the applicant, (III) evidence of suitability for the job, and (IV) what the applicant hopes to gain from the position. 

You can address your application to Dr. Jasmijn Baaijens.

 

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements. 

Please note:

• You can apply online. We will not process applications sent by email and/or post. 
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
• Please do not contact us for unsolicited services.