Stellenbeschreibung
Deep learning has only just started its transformative impact on the natural sciences. In Microsoft Research AI for Science we are seeking to solve some of the fundamental challenges in the molecular sciences with deep learning.
We are seeking a highly motivated Research Engineering Intern. The ideal candidate will have an understanding of machine learning and/or language modelling fundamentals, and will work on language modelling within the context of natural sciences.
Required/Minimum Qualifications:
- Working towards a Bachelor’s or Master's degree or equivalent work experience in Computer Science, Physics, Engineering, Chemistry, Mathematics or a related field.
- Strong familiarity with Linux and the open-source ecosystem
- Experience with scientific computing
Preferred/Additional Qualifications:
- Experience with cloud computing or HPC is a plus
- Experience with language modelling is a plus
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/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
- Architect, design, and implement scalable and robust solutions for machine learning and scientific research involving large volumes of heterogeneous data.
- Build and optimize distributed data processing and model building pipelines.
- Develop and maintain tools and technologies for building, training, optimizing, scaling machine learning solutions