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- Tasks: Drive innovative projects in drug discovery using AI and cheminformatics.
- Company: Join SandboxAQ’s AI Simulation group, revolutionising drug discovery with cutting-edge technology.
- Benefits: Enjoy competitive salary, potential bonuses, and equity options.
- Why this job: Be part of a dynamic team tackling real-world challenges in healthcare and science.
- Qualifications: PhD in relevant fields with 1-5 years of experience in machine learning and computational chemistry.
- Other info: Contribute to scientific publications and present at conferences.
The predicted salary is between 100000 - 140000 £ per year.
Machine Learning Cheminformatics Engineer, Drug Discovery (EMEA) SandboxAQ’s AI Simulation group partners with global research teams to discover new drugs and materials using AI and physics-based computational solutions. We are seeking an experienced researcher to drive innovative and impactful projects leveraging cheminformatics, machine learning, and computational chemistry for drug discovery. The successful candidate will demonstrate strong abilities in cheminformatics and/or bioinformatics, including knowledge of established techniques and cutting-edge machine learning methods for modeling molecular properties and interactions with complex systems. They will also have experience with scientific programming and data science. These skills will be leveraged within a seasoned, agile, and multi-disciplinary group, including drug hunters with an excellent track record in drug discovery, computational chemists, physicists, AI experts, and software engineers. Design and implement software that leverages informatics, machine learning, and computational chemistry to address unmet needs in drug discovery Leverage Bayesian optimization and active learning to improve experimental designs and make data-driven decisions Translate research and applications to maintainable software systems Contribute to the scientific community by writing patents / journal articles and presenting at conferences Translate insights from statistics, multimodal data analysis, and ML to actionable and testable drug discovery hypothesis PhD in chemistry, biology, computer science, or a related discipline ~1-5 years of relevant experience including hands-on experience with informatics, machine learning, and computational chemistry applied to drug discovery in the private sector, like biotech or pharma ~ Experience with molecular property prediction and multi-objective optimization using machine learning and / or deep learning methods ~ Experienced with common python toolkits for scientific computing (e.g., numpy, pandas, scipy), machine learning (e.g., Familiarity running simulations and training models on high-performance computing (GPU) environments for corporate R&D, innovation labs, or academic research ~ An interest in solving scientific problems in chemistry and biology via computational and data-driven methods ~ Hands-on mentality & comfortable with getting deep into the technical weeds of highly complex problems, and a track record of driving projects to completion The US base salary range for this full-time position is expected to be $142k – $198k per year. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity. #
Machine Learning Engineer Data Science employer: Le Lab Quantique
Contact Detail:
Le Lab Quantique Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer Data Science
✨Tip Number 1
Network with professionals in the cheminformatics and drug discovery fields. Attend relevant conferences or webinars where you can meet industry experts and learn about the latest trends. This can help you gain insights into what companies like us at StudySmarter are looking for in candidates.
✨Tip Number 2
Showcase your hands-on experience with machine learning and computational chemistry through personal projects or contributions to open-source initiatives. This practical demonstration of your skills can set you apart from other candidates and highlight your passion for the field.
✨Tip Number 3
Familiarise yourself with the latest tools and technologies used in cheminformatics and drug discovery. Being well-versed in Python toolkits like NumPy, Pandas, and SciPy will not only boost your confidence but also make you a more attractive candidate for our team.
✨Tip Number 4
Prepare to discuss your previous projects in detail during interviews. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your problem-solving abilities and your hands-on mentality, which are crucial for a role like this at StudySmarter.
We think you need these skills to ace Machine Learning Engineer Data Science
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in cheminformatics, machine learning, and computational chemistry. Use specific examples from your past work that demonstrate your skills in these areas, especially any relevant projects in drug discovery.
Craft a Compelling Cover Letter: In your cover letter, express your passion for drug discovery and how your background aligns with the role. Mention specific techniques or projects you've worked on that relate to the job description, such as Bayesian optimization or molecular property prediction.
Showcase Your Technical Skills: Clearly outline your proficiency with programming languages and tools mentioned in the job description, like Python, numpy, pandas, and scipy. Provide examples of how you've used these tools in previous roles to solve complex problems.
Highlight Collaborative Experience: Since the role involves working within a multi-disciplinary team, emphasise any collaborative projects you've been part of. Discuss how you contributed to team success and how you can bring that experience to the new role.
How to prepare for a job interview at Le Lab Quantique
✨Showcase Your Technical Skills
Be prepared to discuss your experience with cheminformatics, machine learning, and computational chemistry in detail. Highlight specific projects where you've applied these skills, especially in drug discovery, and be ready to explain the methodologies you used.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your ability to tackle complex scientific problems. Prepare examples of how you've approached challenges in previous roles, particularly those involving data-driven decision-making and experimental design.
✨Familiarise Yourself with Relevant Tools
Make sure you're well-versed in common Python toolkits like NumPy, Pandas, and SciPy. Be ready to discuss how you've used these tools in high-performance computing environments, as this will be crucial for the role.
✨Prepare for Collaborative Discussions
Since the role involves working within a multi-disciplinary team, be ready to talk about your experience collaborating with professionals from different backgrounds. Highlight any successful projects where teamwork played a key role in achieving results.
