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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, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a collaborative team tackling real-world challenges in immunology and machine learning.
- Qualifications: PhD or MSc in a relevant field with strong machine learning and statistical modelling skills required.
- Other info: Ideal for those passionate about biology and technology, with opportunities for impactful research.
The predicted salary is between 36000 - 60000 £ 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 meetups to connect with 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 specialized subreddits can provide insights into current projects and challenges, helping you to showcase your knowledge during interviews.
✨Tip Number 3
Consider contributing to open-source projects related to machine learning in biology. This not only enhances your skills but also demonstrates your commitment to the field and can make your profile stand out to hiring managers.
✨Tip Number 4
Prepare to discuss specific machine learning models you've worked with, especially those relevant to biological data analysis. Be ready to explain your thought process and the impact of your work on previous projects, as this will show your practical experience and problem-solving abilities.
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 and how it relates to the challenges mentioned in the job description. Be specific about your contributions to past projects.
Showcase Your Publications: If you have peer-reviewed publications, mention them in your application. Highlight any that are particularly relevant to computational biology or machine learning, as this demonstrates your scientific productivity and expertise in the field.
Prepare for Technical Questions: Anticipate technical questions related to machine learning, statistical modelling, and biological data analysis. Be ready to discuss your hands-on experience with tools like TensorFlow or PyTorch, and how you've applied these in previous roles.
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 Collaborative Spirit
Since the role involves working within a collaborative team, share examples of past teamwork experiences. Discuss how you contributed to projects that spanned academic, clinical, and industry domains, showcasing your ability to work well with others.
✨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, demonstrating your analytical thinking.
✨Familiarise Yourself with Current Trends
Stay updated on the latest advancements in computational biology and machine learning, especially in immunology and biologics. Being knowledgeable about current trends will show your passion for the field and your commitment to continuous learning.
