Head of Scientific Operations

6 months ago

Oxford, United Kingdom Ellison Institute of Technology Full time

**Our Mission**

Founded by Larry Ellison and David B. Agus, MD, the Ellison Institute of Technology (EIT) works to develop and deploy advanced technology in pursuit of solving some of humanity’s most challenging and enduring problems. Guided by world leaders, scientists, and entrepreneurs, EIT seeks to accelerate innovation by driving scientific and technological advancements across four humane endeavors: medical sciences and healthcare, food security and sustainable agriculture, clean energy and climate change, and government policy and economics.

Please visit eit.org for more details.

**The Team**

We are a collaborative team of world class AI scientists, data scientists, data and software engineers and technologists within the Ellison Institute of Technology. We work across all of the humane endeavours, supported by world-class and large-scale computer and data platforms.

Our mission is to harness AI to unlock 10x impact in all of the humane endeavours, and to deliver 100x impact in the future through foundational ML research and novel AI approaches.

We unite through deep collaboration across three elements: (1) the expertise of EIT’s scientists and our AI impact teams, (2) deep ties with the world class fundamental AI researchers at Oxford University, and (3) the brilliance of the future leaders funded by the Ellison Scholars network. By doing so, we unlock an additionality that is more than the sum of its parts.

We enable AI to be at the heart of how EIT tackles some of humanity's most pressing and enduring challenges.

**The Role**:
Build and lead a world-class operations team to ensure seamless and effective collaboration across diverse AI teams.

**Strategies**:
**Team Development**: Recruit and retain top talent with varied backgrounds in AI and operations. Identify skills gaps, use data-driven recruitment methods, and provide ongoing training and development opportunities.

**Leading by Example**: Foster a culture of excellence, collaboration, and continuous improvement. Set clear expectations, offer regular feedback, and recognise team achievements.

**Strategic Vision**: Align team objectives with organisational goals and advancements in AI. Develop a strategic plan that includes both short-term and long-term goals, ensuring alignment with AI initiatives and the wider organisational vision.

**Key Metrics**:
Team performance and satisfaction.

Retention rates and skills diversity.

Achievement of strategic milestones.

**Effective Collaboration**

Ensure the additionality flywheel of the AI capability operates effectively, with AI mission projects, AI research teams, and CDT graduate DPhil projects all functioning efficiently and collaboratively.

**Strategies**:
**Process Integration**: Develop streamlined processes for project collaboration and communication. Implement collaborative tools (e.g., shared workspaces, communication platforms) and standardise processes for project initiation and execution.

**Cross-Functional Teams**: Foster interactions between teams to leverage diverse expertise. Schedule regular cross-team meetings, workshops, and collaborative events to share knowledge and updates.

**Feedback Loops**: Create mechanisms for continuous feedback and improvement. Conduct regular reviews, gather feedback from all stakeholders, and implement improvements based on the insights gained.

**Key Metrics**:
Number of cross-team initiatives and collaborations.

Efficiency and speed of project execution.

Feedback scores and process improvements.

**Operational Excellence**

Develop and implement processes to ensure high standards of productivity, reproducibility, and regulatory compliance. Optimise resource allocation, budgeting, and project timelines.

**Strategies**:
**Process Optimisation**: Identify and eliminate inefficiencies in workflows. Map current processes, identify bottlenecks, and implement lean methodologies.

**Resource Management**: Ensure optimal use of resources, including personnel, budget, and time. Develop a resource allocation framework and regularly review budgets and project timelines.

**Compliance and Standards**: Maintain adherence to regulatory requirements and industry best practices. Stay updated on relevant regulations, conduct regular compliance audits, and provide training on standards and regulations.

**Key Metrics**

Productivity metrics (e.g., project completion rates, task efficiency).

Compliance audit results.

Budget adherence and resource utilisation rates.

**Integration**

Ensure multidisciplinary teams work well together, drawing on expertise from all groups within the AI capability and across EIT and Oxford.

**Strategies**:
**Interdisciplinary Collaboration**: Promote knowledge sharing and joint problem-solving across disciplines. Organise cross-disciplinary workshops, seminars, and joint projects.

**Shared Vision and Goals**: Establish common objectives that unite different teams. Develop a unified vision statement and ensure it is

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