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We are on the cusp of a new frontier in which machine learning and artificial intelligence are transforming scientific discovery. We seek to drive major advances in sciences with machine learning, with a focus on ‘fifth paradigm’ scenarios. Through these advances, we aim to empower real-world impact on some of the most pressing problems facing society including climate change, green energy, sustainable materials, and the discovery of new drugs.

AI for Science is a new global team in Microsoft Research focusing on the opportunity to transform scientific modelling and discovery through large-scale deep learning. We aim to advance this frontier and to drive real-world impact at a global scale. The AI for Science team encompasses multiple disciplines across machine learning, engineering, program management, and the natural sciences and spans several sites in Europe.

We seek a passionate and highly motivated team player, with technical program management experience in a relevant field, to help to manage the activities of a highly focused research team.

You will be a self-starter who thrives in ambiguity, with strong attention to detail, an ability to work in a complex technical environment, and a desire to participate in the success of the team. You will play a key interface role between internal and external stakeholders.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Required:

• Bachelor's Degree AND experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience.
• Experience managing cross-functional and/or cross-team projects.
• Exceptional verbal and written communication skills, with the ability to engage and influence stakeholders at all organisational levels.
• Strong analytical and problem-solving abilities, with a demonstrated capacity to resolve complex challenges.
• Excellent interpersonal skills; adept at building networks and navigating global, matrixed organisations and external partnerships.
• Self-starter who thrives in ambiguous, fast-paced environments and can independently drive initiatives.
• Effective influencer and negotiator, able to align diverse teams and interests.

Desirable:

• Bachelor's Degree AND proficient years of experience in engineering, product/technical program management OR equivalent experience.
• Proficient years experience managing cross-functional and/or cross-team projects.
• Experience program managing research teams focused on protein dynamics.
• Experience program managing research teams focused on density functional theory.
• Experience reading and/or writing code (e.g., sample documentation, product demos).
• Industry experience in the field of materials science, drug discovery, large-scale computer simulation, or molecular modelling.
• Familiarity with process improvement methodologies (e.g., Lean, Six Sigma).

#Research #AI for Science

• Drive Project Delivery: Support and coordinate AI for Science research projects, ensuring efficiency, effectiveness, and timely achievement of milestones.
• Facilitate Collaboration: Foster effective teamwork within and across project teams, enabling seamless communication and knowledge sharing.
• Lead External Engagements: Coordinate and manage talks, workshops, and research collaborations with industry and academic partners. Oversee all related legal and compliance processes, including nondisclosure agreements, research collaboration agreements, and experimental validation efforts, to ensure regulatory and organisational standards are met.
• Build Strategic Relationships: Cultivate strong partnerships across Microsoft Research, other Microsoft divisions, and external collaborators to drive alignment and shared success.
• Develop Communications: Prepare and deliver clear, impactful internal and external communications materials to support project visibility and stakeholder engagement.
• Champion Data Governance: Implement and monitor data governance policies, ensuring research data integrity, security, and compliance with best practices.
• Optimise Processes: Identify opportunities for process improvement and apply methodologies to enhance team efficiency and effectiveness.
• Enable Agile Delivery: Act as ‘Scrum Master’ for project teams, supporting lead researchers in decision-making and driving Agile project delivery.
• Oversee Technology Transfer: Manage the transfer of AI models and champion efforts to responsibly release and evaluate AI models externally.