Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead groundbreaking research in AI and materials design, driving innovative solutions.
- Company: Join Microsoft, a leader in technology and innovation, committed to advancing science.
- Benefits: Enjoy flexible work options, competitive perks, and a supportive environment.
- Why this job: Make a real-world impact while collaborating with top experts in an exciting field.
- Qualifications: PhD in relevant fields with a strong publication record and leadership experience required.
- Other info: Microsoft values diversity and is committed to equal opportunity for all applicants.
The predicted salary is between 43200 - 72000 £ per year.
Responsibilities Lead, design, and drive the development of an ambitious, high-impact research agenda in AI and materials design. Spearhead the development, evaluation, and execution of innovative ideas while fostering collaborations within interdisciplinary teams to advance AI for materials design and address real-world challenges. Develop and implement research code to evaluate innovative methodologies or derive novel theoretical and practical contributions to the field. Publish in top-tier venues and contribute to open-source tools that advance the field of AI for science. Qualifications and Skills PhD in machine learning, computational materials science, quantum chemistry, or a related field. Proven track record of leadership in AI research, with publications in venues and conferences such as Nature, Science, NeurIPS, ICML, ICLR, or domain-relevant journals like Nature Materials, Physical Review Series, ACS Series, MRS, APS. Deep understanding of Python, AI approaches for materials discovery, and machine learning approaches for materials design, materials simulation techniques, or computational and experimental design of new materials. Passion and drive to see research have real-world impact on societal challenges. Demonstrated ability to lead cross-functional teams and collaborate across domains. Additional Information Read more about AI for Science: AI for Science Web Site Microsoft Research AI for Science Blog Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form. Benefits and perks may vary depending on employment nature and country. #J-18808-Ljbffr
Principal Researcher - Materials employer: Microsoft
Contact Detail:
Microsoft Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Researcher - Materials
✨Tip Number 1
Network with professionals in the AI and materials science fields. Attend relevant conferences or workshops where you can meet potential colleagues and collaborators. Engaging with others in your field can lead to valuable connections that may help you land the job.
✨Tip Number 2
Showcase your leadership skills by participating in or leading interdisciplinary projects. Highlight any experience you have in guiding teams or initiatives, as this is crucial for the Principal Researcher role. Demonstrating your ability to drive research agendas will set you apart.
✨Tip Number 3
Stay updated on the latest advancements in AI for materials design. Follow key publications and thought leaders in the field. Being knowledgeable about current trends and breakthroughs will not only prepare you for interviews but also show your passion for the subject.
✨Tip Number 4
Engage with open-source projects related to AI and materials science. Contributing to these projects can enhance your practical skills and demonstrate your commitment to advancing the field. It’s a great way to build your portfolio and make a positive impression.
We think you need these skills to ace Principal Researcher - Materials
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your PhD and relevant experience in machine learning, computational materials science, or quantum chemistry. Emphasise any leadership roles you've held in AI research and list your publications in top-tier venues.
Craft a Strong Cover Letter: In your cover letter, express your passion for AI and materials design. Discuss how your background aligns with the responsibilities of the role and mention specific projects where you led interdisciplinary teams or developed innovative methodologies.
Showcase Your Technical Skills: Clearly outline your proficiency in Python and any AI approaches you've used for materials discovery. Include examples of research code you've developed or contributions to open-source tools that demonstrate your technical capabilities.
Highlight Real-World Impact: Discuss how your research has addressed real-world challenges. Provide examples of how your work has had a tangible impact on societal issues, showcasing your drive to see research translate into practical solutions.
How to prepare for a job interview at Microsoft
✨Showcase Your Research Agenda
Be prepared to discuss your vision for a high-impact research agenda in AI and materials design. Highlight any innovative ideas you've developed and how they can address real-world challenges.
✨Demonstrate Leadership Experience
Share specific examples of your leadership in AI research, particularly in interdisciplinary teams. Discuss how you have successfully driven projects and fostered collaboration among diverse groups.
✨Highlight Technical Proficiency
Make sure to emphasise your deep understanding of Python and machine learning approaches relevant to materials design. Be ready to discuss your experience with research code development and methodologies you've implemented.
✨Prepare for Publication Discussions
Since publishing in top-tier venues is crucial, be ready to talk about your past publications. Discuss the impact of your work and how it contributes to the field of AI for science, as well as any open-source tools you've contributed to.
