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- Tasks: Develop machine learning models to analyse complex biological data and drive innovative projects.
- Company: Join a cutting-edge biotech firm dedicated to decoding the immune system.
- Benefits: Enjoy flexible work options, collaborative culture, and opportunities for impactful research.
- Why this job: Be part of a mission-driven team tackling real-world health challenges with advanced technology.
- Qualifications: PhD or MSc in relevant fields; strong ML background and experience with biological data required.
- Other info: Ideal for those passionate about immunology and eager to push scientific boundaries.
The predicted salary is between 43200 - 72000 £ per year.
A cutting-edge biotech organization is seeking highly motivated Computational Scientists to support the mission of decoding and engineering the immune system. The role focuses on developing advanced machine learning and statistical models to analyze complex biological data, particularly immune repertoires and multimodal datasets.
About the Role
- Design and implement machine learning models—particularly language models, diffusion models, or graph neural networks—tailored to biomedical challenges.
- Build novel computational methods for interpreting biological sequences and structural data.
- Customize existing tools and develop new ones for integrative analysis and visualization of large-scale systems immunology data.
- Drive ML-based pipelines for diagnostic or therapeutic design.
- Benchmark computational methods and optimize performance across datasets.
- Lead or contribute to collaborative projects spanning academic, clinical, and industry domains.
Required Qualifications
- PhD (or MSc with equivalent experience) in Computational Biology, Bioinformatics, Computer Science, Statistics, Physics, or related quantitative discipline.
- Strong background in machine learning and statistical modeling, with a demonstrated ability to solve complex biological problems.
- Proven track record of scientific productivity (e.g., peer-reviewed publications).
- Hands-on experience in data handling, visualization, and biological data analysis.
- Proficient in Python, familiar with software development best practices.
- Practical experience with TensorFlow and/or PyTorch.
Preferred Qualifications
- 3+ years post-graduate experience in academia or biotech/pharma, applying ML/AI to biological datasets.
- Prior exposure to immunology, especially TCR/BCR repertoire analysis, or experience with protein design & or biologics.
- Deep expertise in at least one of the following areas:
- Language models for sequence analysis
- Diffusion models in molecular design
- Graph ML in biomedical networks
Computational Biology & Machine Learning Scientist employer: Skills Alliance
Contact Detail:
Skills Alliance Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computational Biology & Machine Learning Scientist
✨Tip Number 1
Network with professionals in the biotech and computational biology fields. Attend relevant conferences, webinars, or workshops to meet potential colleagues and learn about the latest trends in machine learning applications in immunology.
✨Tip Number 2
Engage with online communities and forums focused on computational biology and machine learning. Platforms like GitHub or LinkedIn can be great for showcasing your projects and connecting with others who share your interests.
✨Tip Number 3
Stay updated on the latest research in machine learning and immunology. Reading recent publications and following key researchers in the field can provide insights that you can discuss during interviews, demonstrating your passion and knowledge.
✨Tip Number 4
Prepare to discuss specific projects where you've applied machine learning techniques to biological data. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will showcase your problem-solving skills.
We think you need these skills to ace Computational Biology & Machine Learning Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in computational biology, machine learning, and any specific projects related to immunology or biologics. Use keywords from the job description to align your skills with what the company is looking for.
Craft a Strong Cover Letter: In your cover letter, express your passion for the role and the company's mission. Discuss your experience with machine learning models, particularly those relevant to biomedical challenges, and how you can contribute to their goals.
Showcase Your Publications: If you have peer-reviewed publications, mention them in your application. Highlight any that are particularly relevant to the role, such as those involving machine learning applications in biological data analysis.
Demonstrate Technical Skills: Clearly outline your proficiency in Python and any experience with TensorFlow or PyTorch. If you have worked with GPU computing or have experience in specific areas like language models or graph ML, make sure to include that information.
How to prepare for a job interview at Skills Alliance
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning models, particularly language models, diffusion models, or graph neural networks. Highlight specific projects where you've applied these techniques to solve biological problems.
✨Demonstrate Your Collaborative Spirit
Since the role involves working within a team, share examples of past collaborative projects. Emphasise your ability to work across academic, clinical, and industry domains, showcasing how you contributed to team success.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving skills in computational biology. Be ready to walk through your thought process on how you would approach a complex biological dataset or challenge.
✨Familiarise Yourself with Current Trends
Stay updated on the latest advancements in computational biology and machine learning, especially in immunology. Being able to discuss recent research or breakthroughs can demonstrate your passion and commitment to the field.
