At a Glance
- Tasks: Lead a team to develop AI models that revolutionise drug discovery.
- Company: Join a pioneering biotech firm focused on innovative solutions.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Be part of a groundbreaking team at the forefront of drug discovery.
- Why this job: Make a real impact in healthcare by merging AI with biology.
- Qualifications: PhD in relevant field and proven leadership experience in AI/ML.
The predicted salary is between 100000 - 150000 € per year.
We are looking for a motivated, experienced leader in the Machine Learning and AI space to join this company in their mission to reimagine how drugs are discovered. You will recruit and lead a team focused on building AI foundation models of biology that learn from massive amounts of data, and transfer across several diseases, tissue/cell types, and data types. The team you hire will be focused on genomics foundation models, patient representation learning, and perturbation modelling. We are looking for scientists, strategists, and builders - someone who thrives at the intersection of AI/ML, biology, and leadership.
Your responsibilities may include:
- Defining research agenda for foundation models applied to functional genomics
- Designing novel architectures for multi-modal biological data integration (genomics, transcriptomics, proteomics, clinical)
- Developing self-supervised learning approaches for omics and clinical data
- Collaborate on joint research programme to build architectures where learned representations support causal identifiability
- Lead graph neural network and transformer architecture research for biological networks
- Publish at top ML venues (NeurIPS, ICML, ICLR)
- Present work at conferences and build external reputation for the organization
Must have a PhD in related field, eg Mathematics, Machine Learning, Artificial Intelligence, Statistics etc. Must have significant post PhD experience in an industry setting (eg biotech, techbio, pharmaceutical company). Proven experience building a team of 10 or more - inspiring, influential leader who teams want to follow. Strong understanding of how to build foundational models for drug discovery (this will not be a hands-on role but you have to know what good looks like). Significant experience managing stakeholders from diverse backgrounds. Experience building tools that have impact on the pipeline (not just building for the sake of it).
This is a genuinely fantastic opportunity for an experienced leader to join this company right at the start, and play a key role in building this hub and steering their strategic direction.
Director of Machine Learning employer: KEMIO Consulting
Join a pioneering company at the forefront of drug discovery, where your leadership in Machine Learning will directly impact the future of healthcare. With a hybrid work model based in London, we foster a collaborative and innovative culture that prioritises employee growth through continuous learning and development opportunities. As part of our team, you will not only lead cutting-edge research but also shape a dynamic environment that values creativity and scientific excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Director of Machine Learning
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and biotech fields. Attend meetups, conferences, or webinars where you can chat with industry leaders and potential colleagues. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your expertise! Create a portfolio or a personal website showcasing your projects, research, and any publications. This is your chance to demonstrate your knowledge in machine learning and biology, making you stand out to hiring managers.
✨Tip Number 3
Prepare for interviews by brushing up on your leadership skills. Be ready to discuss how you've built and inspired teams in the past. Use specific examples that highlight your experience in managing diverse stakeholders and driving impactful projects.
✨Tip Number 4
Don't forget to apply through our website! We’re always on the lookout for talented individuals like you. Make sure your application reflects your passion for AI and drug discovery, and let us know how you can contribute to our mission.
We think you need these skills to ace Director of Machine Learning
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the specific skills and experiences that align with the Director of Machine Learning role. Highlight your leadership experience, especially in building teams and working with AI/ML in a biological context.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about drug discovery and how your background makes you the perfect fit for this role. Be sure to mention any relevant projects or research you've led.
Showcase Your Research Impact:Since publishing at top ML venues is part of the gig, include any significant publications or presentations in your application. This will demonstrate your expertise and commitment to advancing the field.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity right from the start!
How to prepare for a job interview at KEMIO Consulting
✨Know Your Stuff
Make sure you brush up on the latest trends in machine learning and AI, especially as they relate to drug discovery. Be ready to discuss foundational models and how they can be applied to genomics and other biological data. This shows you're not just a leader but also someone who understands the technical side of things.
✨Showcase Your Leadership Skills
Prepare examples of how you've successfully built and led teams in the past. Highlight your ability to inspire and influence others, as this role requires someone who can rally a team around a common goal. Think about specific challenges you've faced and how you overcame them.
✨Engage with Stakeholders
Since managing diverse stakeholders is key, come prepared with examples of how you've navigated complex relationships in previous roles. Discuss how you’ve communicated effectively with different teams and ensured everyone is aligned towards the same objectives.
✨Be Ready to Discuss Research
Given the emphasis on publishing and presenting at top ML venues, be prepared to talk about your past research and its impact. Bring up any relevant publications or presentations, and think about how you can contribute to the company's research agenda moving forward.
