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For Companies At a Glance
- Tasks: Develop AI co-pilots and models for complex biological research.
- Company: Join a pioneering AI biotech firm revolutionising drug discovery and healthcare.
- Benefits: Enjoy a hybrid work environment with competitive salary and collaborative culture.
- Why this job: Shape the future of AI in biology and impact patient lives globally.
- Qualifications: MSc in Machine Learning or related field; experience with LLMs and deep learning frameworks required.
- Other info: Opportunity to publish high-impact research and contribute to patents.
The predicted salary is between 68000 - 102000 £ per year.
The Company
Our client is a pioneering AI biotech ecosystem on a mission to revolutionise biological research and drug discovery. At the forefront of agentic AI, their multidisciplinary teams are driving cutting-edge innovations in healthcare through next-generation machine learning and biological intelligence. They combine advanced AI, rich multimodal datasets, and domain-specific expertise in biology. Home to a unique AI co-pilot platform that powers breakthroughs in therapeutic research, they offer a dynamic, high-growth environment with a collaborative and international culture, focused on long-term scientific challenges that impact patient lives globally.
The Role
This is a rare opportunity to shape the next wave of agent-based AI in biology. You’ll be at the core of developing new AI co-pilots, using sophisticated models to understand complex biology, and contributing to the emergence of Biological Artificial Superintelligence. Responsibilities include:
- Designing and applying agent-based models across large, multimodal patient datasets
- Collaborating with top-tier scientists and engineers to build AI systems tailored for biomedical discovery
- Contributing to long-term research programs focused on autonomous AI agents
- Leading and implementing state-of-the-art ML methods into a therapeutic platform
- Publishing high-impact research and supporting the development of patents
Your Experience
MSc (or equivalent) in Machine Learning, Computer Science, or related field. Proven track record with LLMs, generative AI, optimization, or sequential learning. Experience with deep learning frameworks (TensorFlow, PyTorch, JAX, etc.). Expertise in one or more: reinforcement learning, Bayesian optimization, optimal experimental design, agents, or causality. Experience in drug/target discovery, treatment modeling, or medical AI research. Publications in high-impact conferences or journals highly desirable.
Next Steps
This Agentic AI Scientist role is attracting strong interest, so please get in touch soon or hit the apply button. If you have any questions or need career advice, don’t hesitate to reach out—we’d love to connect.
Senior AI Research Scientist employer: KDR Talent Solutions
Contact Detail:
KDR Talent Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Research Scientist
✨Tip Number 1
Network with professionals in the biotech and AI fields. Attend relevant conferences, webinars, or meetups to connect with potential colleagues and industry leaders. This can help you gain insights into the company culture and the specific challenges they face.
✨Tip Number 2
Showcase your expertise in agent-based models and machine learning during informal discussions or networking events. Be prepared to discuss your previous projects and how they relate to the role, as this demonstrates your passion and knowledge in the field.
✨Tip Number 3
Engage with the company's online presence. Follow them on social media, comment on their posts, and share relevant content. This not only shows your interest but also helps you stay updated on their latest developments and initiatives.
✨Tip Number 4
Prepare for potential interviews by brushing up on the latest advancements in AI and biotechnology. Familiarise yourself with their AI co-pilot platform and think about how your skills can contribute to their mission of revolutionising drug discovery.
We think you need these skills to ace Senior AI Research Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI, machine learning, and biotech. Emphasise any projects or roles that demonstrate your expertise in agent-based models and deep learning frameworks.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI in the biotech field. Discuss specific experiences that align with the job description, such as your work with LLMs or publications in high-impact journals.
Highlight Collaborative Experience: Since the role involves collaboration with scientists and engineers, mention any previous teamwork experiences. Describe how you contributed to projects and the outcomes of those collaborations.
Showcase Research Contributions: If you have published research, summarise your contributions and their impact. Highlight any patents or innovative solutions you've developed, as this will demonstrate your capability to contribute to long-term research programs.
How to prepare for a job interview at KDR Talent Solutions
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with machine learning frameworks like TensorFlow or PyTorch. Highlight specific projects where you've applied LLMs or generative AI, and be ready to explain the methodologies you used.
✨Demonstrate Collaborative Skills
Since the role involves working with top-tier scientists and engineers, share examples of successful collaborations from your past. Emphasise your ability to communicate complex ideas clearly and work effectively in a team.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving skills, particularly in relation to agent-based models and biological datasets. Practice articulating your thought process and how you approach complex challenges in AI and biology.
✨Discuss Your Research Impact
If you have publications, be ready to discuss their significance and how they relate to the role. Talk about your contributions to high-impact research and how you envision applying that knowledge to the company's mission.
