At a Glance
- Tasks: Lead the development of AI systems to revolutionise drug discovery.
- Company: Valence Labs, a pioneer in scientific discovery and machine learning.
- Benefits: Inclusive culture, competitive salary, and opportunities for professional growth.
- Other info: Join a diverse team passionate about pushing ML boundaries.
- Why this job: Make a real impact on healthcare by applying cutting-edge ML research.
- Qualifications: PhD or Master's with 3+ years in ML and strong programming skills.
The predicted salary is between 60000 - 80000 £ per year.
We’re seeking an experienced Research Engineer to shape and lead the development of software and AI systems that will help in our mission of industrializing scientific discovery to radically improve lives. We're looking for individuals with strong engineering skills, including expertise in designing, implementing, improving, and deploying distributed machine learning systems at significant scale. In addition, we highly value proficiency with state-of-the-art machine learning algorithms and exceptional problem solving skills.
In this role, you will:
- Support Valence Labs’ research agenda across ML for drug discovery.
- Engage with and contribute to open-source libraries developed by Valence and the research community.
- Create and improve novel ML methods that will accelerate drug discovery.
- Collaborate with an interdisciplinary team of dry and wet lab scientists to inform and improve our models and systems.
- Present and communicate research findings through talks, blog posts, publications, and conferences.
A successful candidate will have most of the following:
- PhD or Master's degree with 3+ years of industry experience.
- Strong programming skills and understanding of modern software development practices, especially in Python.
- Scientific knowledge of biology, chemistry, or physics along with previous experience working in a scientific environment across disciplines.
- Experience with real world natural science data and the associated challenges.
- Experience with high throughput bioassay data such as next-generation sequencing data, cellular imaging data, proteomics data or similar.
- Proven track record in machine learning, including multimodal learning, designing new architectures, hands-on experimentation, analysis, visualization, and model deployment.
- Demonstrated capability to understand and summarize scientific content and implement deep learning models based on descriptions from publications.
- Strong knowledge of linear algebra, calculus, and statistics.
- Passion for applying ML research to real-world problems.
Nice to have:
- Experience in building and deploying high-performance implementations of deep learning algorithms.
- Authorship of publications in peer-reviewed conferences (e.g., NeurIPS, ICML, or ICLR) or journals (e.g. Nature, Science, JACS, or ACS).
- Contribution to high-visibility ML codebases.
Valence Labs is committed to creating a diverse and inclusive environment, where understanding and accommodating personal needs and preferences is a priority. Join our multidisciplinary team of passionate researchers, eager to push the boundaries of ML research and contribute to industrializing scientific discovery to radically improve lives.
Senior Multimodal ML Research Engineer for Drug Discovery employer: Valence Labs
Valence Labs is an exceptional employer that fosters a collaborative and inclusive work culture, where innovation thrives and diverse perspectives are valued. As a Senior Multimodal ML Research Engineer, you will have the opportunity to work at the forefront of drug discovery, contributing to groundbreaking research while enjoying robust professional development opportunities and a supportive environment that prioritises employee well-being. Located in a vibrant area, our team is dedicated to pushing the boundaries of machine learning to make a meaningful impact on lives worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Multimodal ML Research Engineer for Drug Discovery
✨Tip Number 1
Network like a pro! Reach out to folks in your field on LinkedIn or at conferences. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML and drug discovery. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your problem-solving skills. Expect technical questions that test your knowledge of ML algorithms and software development practices. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our mission.
We think you need these skills to ace Senior Multimodal ML Research Engineer for Drug Discovery
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the role. Highlight your expertise in machine learning, programming, and any relevant scientific knowledge. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about drug discovery and how your background makes you a perfect fit for our team. Be genuine and let your enthusiasm show!
Showcase Your Projects:If you've worked on any interesting projects, especially those related to ML or drug discovery, make sure to mention them. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at Valence Labs!
How to prepare for a job interview at Valence Labs
✨Know Your Stuff
Make sure you brush up on the latest advancements in multimodal machine learning and drug discovery. Be ready to discuss specific algorithms and their applications, as well as any relevant projects you've worked on. This shows your passion and expertise in the field.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled complex problems in previous roles. Think about challenges you've faced with real-world scientific data and how you approached them. This will demonstrate your analytical thinking and ability to innovate.
✨Collaborate Like a Pro
Since this role involves working with interdisciplinary teams, be ready to discuss your experience collaborating with scientists from different backgrounds. Highlight any successful projects where teamwork was key, and how you communicated complex ideas effectively.
✨Engage with the Community
If you've contributed to open-source libraries or published research, make sure to mention it! Talk about your involvement in the ML community and how it has shaped your work. This not only showcases your skills but also your commitment to advancing the field.
