Lead Machine Learning Researcher

JR United Kingdom; London; On-site; GBP 60,000 - 100,000; Full time

Job summary

An innovative firm is seeking a Lead Machine Learning Researcher to drive advancements in drug discovery through cutting-edge multi-omics integration. This role involves developing novel cell embeddings and designing deep learning models that leverage diverse omics data, enabling precise predictions of drug effects. You will collaborate with experts in bioinformatics and AI, contributing to scientific publications and leading research initiatives. If you are passionate about applying machine learning to real-world challenges in healthcare, this opportunity offers a dynamic environment to make a significant impact.

Qualifications

• PhD or Postdoc in Computer Science with publications in top ML conferences.
• Strong background in machine learning and applied mathematics.

Responsibilities

• Design deep learning models integrating diverse omics data.
• Collaborate with experts to validate models and integrate data.

Skills

Machine Learning

Deep Learning

Bioinformatics

Data Integration

Collaboration

Education

PhD in Computer Science

Postdoc in related fields

Job description

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Lead Machine Learning Researcher, London

Client:

Skills Alliance

Location:

London, United Kingdom

Job Category:

Other

EU work permit required:

Yes

Job Views:

8

Posted:

18.04.2025

Expiry Date:

02.06.2025

Job Description:

Develop novel cell embeddings that integrate multi-omics foundation models—transcriptomics, proteomics, epigenomics, and metabolomics—to capture comprehensive cellular signatures. Your work will enable precise predictions of drug effects, driving innovation in drug discovery.

Key Responsibilities:

1. Model Development: Design deep learning models integrating diverse omics data to create robust cell embeddings for digital twin technology.
2. Multi-Omics Integration: Develop and refine foundation models across omics platforms into a unified cell representation.
3. Collaboration: Work with experts in bioinformatics, drug discovery, and AI to validate models and integrate multi-modal data.
4. Client & Partner Engagement: Support product and service teams in translating AI models into real-world drug discovery applications.
5. Research Leadership: Stay at the forefront of AI and omics advancements, contributing to scientific publications and innovation.

Preferred Qualifications:

1. PhD/Postdoc in Computer Science (or related fields): Publications in top ML conferences (e.g., NeurIPS, ICLR, ICML, CVPR).
2. Strong ML/Applied Math Background: Expertise in advanced ML techniques.
3. Deep Learning Experience: Building and scaling AI models for omics or high dimensional biological data.
4. Collaborative Mindset: Track record of success in interdisciplinary teams and cross-functional projects.