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Data Scientist II

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Worcester

On-site

GBP 40,000 - 80,000

Full time

8 days ago

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Job summary

An innovative firm is seeking a talented Data Scientist to join its Spatial Omics team. This role involves developing computational methods for analyzing image-based spatial omics datasets, integrating multi-modal data, and contributing to drug discovery research. The successful candidate will work in a dynamic environment alongside pathologists and research scientists, focusing on innovative projects that aim to identify disease biomarkers and therapeutic targets. If you are passionate about bioinformatics and eager to make an impact in the life sciences, this opportunity is perfect for you.

Qualifications

  • Ph.D. in Computational Biology or equivalent experience required.
  • Strong programming skills in Python, R, or MATLAB essential.

Responsibilities

  • Develop computational pipelines for spatial omics datasets analysis.
  • Collaborate with pathologists to validate spatial analysis tools.

Skills

Python
R
MATLAB
Analytical Skills
Problem-solving
Communication Skills

Education

Ph.D. in Computational Biology
Equivalent experience in Bioinformatics

Tools

NumPy
Pandas
Matplotlib
Scikit-learn
Squidpy
Scanpy
Visopharm
Qupath
BioTuring
AWS

Job description

Job Description

Company Description:

  • Katalyst Healthcares & Life Sciences is hiring entry level candidates for several positions for contract research in Clinical trials of drugs, biologics and medical devices.
  • We have a few immediate job opportunities available in Drug Safety and Pharmacovigilance and Clinical Research field. We work with University hospitals, pharmaceutical companies and recruiting partners.

Job Description:

We seek a talented and highly motivated Data Scientist to join our expanding Spatial omics team within the Discovery Immunology Pathology group. The successful candidate will develop and apply computational methods for the analysis of image-based spatial omics datasets, including the integration of multi-modal omics data and data interpretation in order to derive novel biological insights, identify disease biomarkers and new therapeutic targets. The successful candidate will be part of a unique multidisciplinary team working closely with pathologists, image analysts, and research scientists across the organization in a highly dynamic and collaborative environment to support pathology driven spatial omics projects that contribute to innovative drug discovery research.

Responsibilities:

  • Design, develop and implement computational pipelines for processing and analyzing spatial omics datasets, including spatial transcriptomics and proteomics.
  • Collaborate with pathologists and image analysts to develop methods to integrate and analyze spatial transcriptomics data with other spatial modalities, such as IHC or mIF.
  • Collaborate with pathologists to validate spatial analysis tools in the context of tissue structure to ensure accuracy and reproducibility.
  • Ensure scalability and efficiency of the pipelines to handle large and complex datasets.
  • Lead the development of data visualization tools to effectively communicate findings to both technical and non-technical stakeholders.
  • Stay current with emerging trends and technologies in spatial omics and bioinformatics and assess their applicability to ongoing projects.
  • Generate concise reports and accurately document project details, algorithms and results in electronic laboratory notebook.

Requirements:

  • Ph.D. (or equivalent experience) in Computational Biology, Bioinformatics, Systems Biology, or a related field. Background in life sciences or experience in the pharmaceutical industry.
  • Strong proficiency in programming such as Python, R, or MATLAB, and relevant data science libraries (such as NumPy, Pandas, Matplotlib, Scikit-learn, etc.) for data analysis, manipulation, and visualization.
  • Experience with bioinformatics tools and databases, especially those pertinent to omics data analysis such as Squidpy or Scanpy.
  • Excellent analytical, problem-solving, and communication skills.
  • Ability to work independently and as part of a team, managing multiple projects simultaneously.
  • Familiarity with digital pathology image analysis platforms (Visopharm and Qupath) and spatial omics analytic platforms (BioTuring).
  • Experience with machine learning frameworks and data visualization tools.
  • Familiarity with cloud-based (AWS) and high-performance computing environments.

Additional Information:

All your information will be kept confidential according to EEO guidelines.

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