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Senior Data Engineer, AI for Science
vor 4 Monaten
Overview
Over the coming decade, deep learning looks set to have a transformational impact on the natural sciences. The consequences are potentially far-reaching and could dramatically improve our ability to model and predict natural phenomena over widely varying scales of space and time. Our team encompasses world experts in machine learning, computational chemistry, material science, quantum physics, molecular biology, software engineering, and other disciplines, who are working together to tackle some of the most pressing challenges in this field.
For our lab in Berlin, Germany, we are seeking Senior Data Engineer candidates in the area of deep learning for computational chemistry. The successful applicant is expected to contribute to the development of cutting-edge synthetic datasets for chemistry based on quantum chemistry simulations, which has the potential to unlock breakthrough deep-learning models for a broad range of applications.
This is an exceptional opportunity to participate in ambitious research in a highly collaborative, diverse and global team of other researchers and engineers, to push the state of the art in deep learning for the natural sciences.
There is no closing deadline for this post. The post will be filled once suitable candidates are found so if you are interested, please apply as soon as possible. When submitting your application, include your CV with a list of open-source software contributions as an attachment.
Qualifications
Required Qualifications & Skills:
Completed MSc degree in computer science, mathematics, physics, chemistry, or a similar technical achievement.Proficiency in collaborative software engineering, specifically in Python, preferably with data science flavor and in an industrial team. Experience with cloud-based data solutions and services (databases, object storage, etc).
Recommended Qualifications:
Experience with large-scale data generation or acquisition for machine learning.Read more about MSR AI for Science:
#Research #AI for Science
Responsibilities
Contribute to development of cutting-edge synthetic datasets for chemistry based on computational chemistry simulations. Work closely with domain experts to translate computational chemistry software into large-scale cloud-based data generation pipelines. Design and develop large-scale cloud-based data storage and organization solutions for scientific data. This includes infrastructure development, dataset handling, data visualization, and resource management. Coordinate with researchers to design and implement efficient and effective data pipelines to consume data in deep learning and data analysis tasks to maximize research velocity. Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.Industry leading healthcareEducational resourcesDiscounts on products and servicesSavings and investmentsMaternity and paternity leaveGenerous time awayGiving programsOpportunities to network and connect