At a Glance
- Tasks: Develop algorithms for cutting-edge single-cell proteomics and collaborate with scientists.
- Company: Join EMBL-EBI, a leader in biological data analysis and innovation.
- Benefits: Enjoy competitive salary, flexible working, and generous leave.
- Why this job: Make a real impact in science and tackle global challenges.
- Qualifications: Strong background in computational proteomics and programming skills in Python and C++.
- Other info: Collaborative environment with excellent career growth and international opportunities.
The predicted salary is between 3000 - 3600 £ per month.
Are you a motivated computational scientist passionate about developing algorithms for cutting-edge proteomics? We are looking for an enthusiastic Computational Proteomics Scientist to join the Proteomics and Metabolomics Team at the European Bioinformatics Institute (EMBL-EBI). The successful candidate will contribute to the development of algorithms, computational resources, and community standards for single-cell proteomics, working at the interface of data science, software engineering, and biological discovery.
Our team is responsible for the development and maintenance of world-leading proteomics resources, including PRIDE, a founding member of the ProteomeXchange Consortium, which captures and disseminates large-scale proteomics data from the global scientific community. We are also major contributors to international standardisation efforts through the Proteomics Standards Initiative (PSI). Single-cell proteomics is an emerging and rapidly evolving field, generating complex, sparse, and large-scale datasets. You will play a key role in designing scalable computational methods and standards to support robust analysis, reproducibility, and FAIR data sharing for next-generation proteomics experiments.
Your Role
- Design and develop algorithms for single-cell proteomics data analysis, including peptide/protein quantification, normalisation, missing value handling, batch correction, and quality control.
- Develop scalable and high-performance software components in Python and C++ for processing large-scale and high-dimensional proteomics datasets.
- Contribute to machine learning and deep learning approaches for proteomics data analysis, including representation learning, denoising, feature selection, and integrative multi-omics analysis.
- Participate in the definition and implementation of community data standards, formats, and APIs for single-cell proteomics under the umbrella of the Proteomics Standards Initiative.
- Work closely with experimental scientists and software engineers to integrate algorithms into production-ready workflows, databases, and cloud-based infrastructures.
- Support the transformation of proteomics resources into AI-ready datasets, enabling downstream use by advanced analytics and large-scale machine learning systems.
- Collaborate with other EMBL-EBI teams and international partners to integrate single-cell proteomics data with resources such as Expression Atlas and UniProt.
You Have
- A strong background in computational proteomics, bioinformatics, computer science, or a related quantitative discipline, with typically 3+ years of relevant research or industry experience.
- Strong experience in mass spectrometry-based proteomics, ideally including single-cell or low-input proteomics.
- Proven experience developing algorithms for proteomics data analysis.
- Excellent programming skills in Python and C++, with a focus on performance, maintainability, and reproducibility.
- Experience with machine learning and/or deep learning frameworks (e.g. PyTorch, TensorFlow, JAX, scikit-learn).
- Solid understanding of statistical methods for high-dimensional and sparse biological data.
- Experience working with large-scale datasets, including efficient I/O and memory-aware data processing.
- Proficiency with version control systems such as Git.
- Ability to work independently, manage multiple priorities, and communicate results clearly in an international environment.
You May Also Have
- Experience with proteomics data formats and standards (e.g. mzML, mzIdentML, mzTab, Parquet-based formats).
- Familiarity with high-performance computing (HPC), GPU acceleration, or parallel computing.
- Experience with workflow systems (e.g. Nextflow) and containerised environments (Docker, Singularity).
- Knowledge of cloud-based infrastructures and scalable data processing frameworks.
- Interest in FAIR data principles, open science, and community-driven standardisation.
- Experience integrating proteomics data with other omics modalities (e.g. transcriptomics, metabolomics).
Contract length: This position is project-based and offered as a fixed-term contract until 04 January 2029.
Salary: Grade 5, monthly starting salary at £3,303 – £3,638 per month after tax but excluding pension and insurance contributions. Plus, generous benefits.
Next Steps: This vacancy will be advertised from Tuesday, 20th January with a scheduled closing date of Tuesday, 3rd February. We welcome your application as soon as possible. Please provide an up-to-date CV and cover letter.
Why join us
At EMBL-EBI you can apply your talent and passion to accelerate science and tackle some of humankind's greatest challenges. EMBL-EBI, part of the European Molecular Biology Laboratory, is a worldwide leader in the storage, analysis and dissemination of large biological datasets. We provide the global research community with access to publicly available databases and tools which are crucial for the advancement of healthcare, food security, and biodiversity.
Enjoy Lots Of Benefits
- Financial incentives: Monthly family, child and non-resident allowances, annual salary review, pension scheme, death benefit, long-term care, accident-at-work and unemployment insurances.
- Flexible working arrangements – including hybrid working patterns.
- Private medical insurance for you and your immediate family (including all prescriptions and generous dental & optical cover).
- Generous time off: 30 days annual leave per year, in addition public holidays.
- Relocation package including installation grant (if required).
- Campus life: Free shuttle bus to and from work, on-site library, subsidised on-site gym and cafeteria, casual dress code, extensive sports and social club activities (on campus and remotely).
- Family benefits: On-site nursery, 10 days of child sick leave, generous parental leave, holiday clubs on campus and monthly family and child allowances.
- Benefits for non-UK residents: Visa exemption, education grant for private schooling, financial support to travel back to your home country every second year and a monthly non-resident allowance.
For detailed information please visit our employee benefits page here.
What else you need to know
- International applicants: We recruit internationally and successful candidates are offered visa exemptions.
- Diversity and inclusion: At EMBL, we believe that diverse teams drive innovation and scientific excellence. We encourage applications from candidates of all genders, identities, nationalities and/or any other diverse backgrounds.
How to apply: To apply please submit a cover letter and a CV through our online system. Applications will close at 23:59 CET on the date shown below. We aim to provide a response within two weeks after the closing date.
Closing Date: 03 / 02 / 2026
Computational Proteomics Scientist employer: European Bioinformatics Institute | EMBL-EBI
Contact Detail:
European Bioinformatics Institute | EMBL-EBI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computational Proteomics Scientist
✨Tip Number 1
Network like a pro! Reach out to folks in the field of computational proteomics, attend relevant meetups or webinars, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving algorithms for proteomics data analysis. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with Python, C++, and machine learning frameworks. Practice explaining complex concepts in simple terms – it’s all about communication!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team at EMBL-EBI.
We think you need these skills to ace Computational Proteomics Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in computational proteomics and relevant programming skills. We want to see how your background aligns with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to express your passion for proteomics and how you can contribute to our team. Be specific about your skills and experiences that relate to the job description.
Showcase Your Projects: If you've worked on any relevant projects, especially those involving algorithms or data analysis, make sure to mention them. We love seeing practical examples of your work and how you tackle complex problems!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way to ensure we receive all your materials and can review them properly. Plus, it shows you’re keen on joining us at EMBL-EBI!
How to prepare for a job interview at European Bioinformatics Institute | EMBL-EBI
✨Know Your Algorithms
Make sure you brush up on the algorithms relevant to single-cell proteomics. Be ready to discuss your experience with peptide/protein quantification, normalisation, and batch correction. Showing a deep understanding of these concepts will impress the interviewers.
✨Showcase Your Coding Skills
Since strong programming skills in Python and C++ are essential, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges that focus on performance and maintainability.
✨Familiarise Yourself with Community Standards
Understanding community data standards and formats like mzML and mzIdentML is crucial. Be prepared to discuss how you've contributed to or implemented these standards in your previous work, as this shows your commitment to collaboration and open science.
✨Prepare for Interdisciplinary Collaboration
Since the role involves working closely with experimental scientists and software engineers, think of examples where you've successfully collaborated across disciplines. Highlight your communication skills and how you can bridge the gap between computational and experimental teams.