Proteomics Data Scientist (1-Year Fixed-Term)

Proteomics Data Scientist (1-Year Fixed-Term)

Full-Time 35000 - 45000 Β£ / year (est.) No working from home possible
Portal Biotech

At a Glance

  • Tasks: Apply machine learning and statistical techniques to proteomics data in a collaborative environment.
  • Company: Portal Biotech, a leader in innovative bioinformatics solutions.
  • Benefits: Gain hands-on experience, competitive salary, and opportunities for professional growth.
  • Other info: Fast-paced research setting with potential for impactful discoveries.
  • Why this job: Join a dynamic team and contribute to groundbreaking research in proteomics.
  • Qualifications: Experience in data science, machine learning, and strong communication skills.

The predicted salary is between 35000 - 45000 Β£ per year.

Portal Biotech is seeking a Data Scientist to join the Bioinformatics & Machine Learning team in the UK.

The role collaborates with the wet lab to apply statistical and machine learning techniques to a single-molecule proteomics platform, spanning exploratory analyses to production-ready pipelines.

You will design pipelines, benchmark methods, and communicate results to both technical and non-technical audiences in a fast-moving research environment.

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Proteomics Data Scientist (1-Year Fixed-Term) employer: Portal Biotech

Portal Biotech is an excellent employer for those looking to grow their finance career in a dynamic startup environment. With a strong focus on employee development, you will have the opportunity to enhance your skills in various finance areas while working with modern systems like Xero and Sage Intacct. Our collaborative work culture encourages innovation and offers flexibility through hybrid working arrangements, making it a rewarding place to contribute and thrive.

Portal Biotech

Contact Details:

Portal Biotech Recruitment Team

We think you need these skills to ace Proteomics Data Scientist (1-Year Fixed-Term)

Python
SQL
Problem-Solving Skills
Communication Skills
Data Engineering
Automation
Data Pipeline Development