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- Tasks: Develop AI models for drug discovery using multi-omics data.
- Company: Join Skills Alliance, a leader in AI and biotechnology staffing.
- Benefits: Enjoy full-time work with opportunities for innovation and collaboration.
- Why this job: Be at the cutting edge of AI and drug discovery, making a real impact.
- Qualifications: PhD/Postdoc in Computer Science or related fields; strong ML background required.
- Other info: Ideal for those passionate about research and interdisciplinary teamwork.
The predicted salary is between 30000 - 42000 £ per year.
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:
- Model Development: Design deep learning models integrating diverse omics data to create robust cell embeddings for digital twin technology.
- Multi-Omics Integration: Develop and refine foundation models across omics platforms into a unified cell representation.
- Collaboration: Work with experts in bioinformatics, drug discovery, and AI to validate models and integrate multi-modal data.
- Client & Partner Engagement: Support product and service teams in translating AI models into real-world drug discovery applications.
- Research Leadership: Stay at the forefront of AI and omics advancements, contributing to scientific publications and innovation.
Preferred Qualifications:
- PhD/Postdoc in Computer Science (or related fields): Publications in top ML conferences (e.g., NeurIPS, ICLR, ICML, CVPR).
- Strong ML/Applied Math Background: Expertise in advanced ML techniques.
- Deep Learning Experience: Building and scaling AI models for omics or high dimensional biological data.
- Collaborative Mindset: Track record of success in interdisciplinary teams and cross-functional projects.
Seniority level: Entry level
Employment type: Full-time
Job function: Research and Science
Industries: Biotechnology Research and Pharmaceutical Manufacturing
Machine Learning Engineer employer: Skills Alliance
Contact Detail:
Skills Alliance Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and omics technologies. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the biotechnology and pharmaceutical sectors. Attend relevant conferences or webinars where you can meet experts and learn about their experiences, which could give you insights into the job and the company culture.
✨Tip Number 3
Showcase your collaborative mindset by participating in interdisciplinary projects or hackathons. Highlighting these experiences can demonstrate your ability to work effectively in teams, which is crucial for this role.
✨Tip Number 4
Stay updated on the latest publications in top ML conferences. Being knowledgeable about current research can help you discuss relevant topics during interviews and show your passion for the field.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and qualifications required for the Machine Learning Engineer position. Familiarise yourself with terms like 'multi-omics' and 'cell embeddings' to demonstrate your knowledge in your application.
Tailor Your CV: Highlight relevant experience in machine learning, deep learning, and any projects related to omics data. Make sure to include specific examples of your work that align with the job description, such as publications or projects that showcase your expertise.
Craft a Compelling Cover Letter: Use your cover letter to explain why you're passionate about the role and how your background fits the company's needs. Mention your collaborative mindset and any interdisciplinary projects you've worked on, as these are key aspects of the job.
Proofread and Edit: Before submitting your application, carefully proofread all documents for spelling and grammatical errors. A polished application reflects your attention to detail and professionalism, which is crucial in a research-focused role.
How to prepare for a job interview at Skills Alliance
✨Showcase Your Technical Skills
Be prepared to discuss your experience with deep learning models and multi-omics data. Highlight specific projects where you've successfully integrated diverse datasets, as this will demonstrate your technical expertise and relevance to the role.
✨Demonstrate Collaborative Experience
Since collaboration is key in this role, share examples of how you've worked with interdisciplinary teams. Discuss any cross-functional projects you've been involved in, especially those related to bioinformatics or drug discovery.
✨Stay Updated on Industry Trends
Research the latest advancements in AI and omics before your interview. Being knowledgeable about current trends and breakthroughs will show your passion for the field and your commitment to staying at the forefront of technology.
✨Prepare Questions for Your Interviewers
Think of insightful questions to ask during the interview. Inquire about the company's approach to integrating AI in drug discovery or their future projects in multi-omics. This shows your genuine interest in the role and the organisation.
