Head of Ai Research

hace 3 semanas

Barcelona, España AstraZeneca A tiempo completo

**Job title**:Senior Director, Head of AI Research

**Location**:Gothenburg (Sweden), Cambridge (UK), Gaithersburg (USA), Barcelona (Spain), Mississauga (Canada)

**What you**’**ll do**

In this role, you will work closely with our Machine Intelligence and Machine Perception groups in developing an exceptional research program that will boost innovation across the organization. You will be required to ensure that the products and services being developed across the Centre for AI, incorporate state-of-the-art in machine learning, establish appropriate benchmarks and metrics, and enforce a rigorous peer review and quality assessment. This will include contributing with novel ideas, design and execution of machine learning projects, with the adherence to the latest methods and engineering best practices and way of working. You will also be expected to collaborate with Machine Intelligence and Machine Perception to drive forward a cohesive program of basic, fundamental, and applied research. The role also gives you an opportunity to realize your ideas in products and services used across clinical trials, drug discovery and the development pipeline.
- Driving innovation and scientific excellence in the department through internal scientific development and external collaboration
- Propose, establish and manage external partnerships, including academic partnership
- Contribute to the leadership of the Center for AI, including design and execution of the CAI strategy
- Provide thought leadership on modern AI and ML engineering practices in the Center for AI and the broader AZ community
- Communicate the strategy of Center for AI to a wide variety of internal and external partners
- Continue to actively engage in ML research with and through the broader ML research community. Publish papers at the major ML conferences, contribute technical blogs and forge strategic alliances with academia and other industry
- Remain at the cutting edge of ML research, especially in a chosen subfield (e.g., deep learning, probabilistic and Bayesian machine learning, active learning, generative models, graph neural networks, NLP, reinforcement learning, etc.).

**Essential for the role**
- PhD degree in computer science, electrical engineering, statistics, applied mathematics, or a related field.
- At least 10 years of experience in developing machine learning models (a minimum of 5 years industry experience after completion of PhD studies).
- ML Ops experience: model tracking, model governance, multiple models in different production contexts
- End-to-end experience leading collaborative ML/data science projects in an industry setting.
- Demonstrated an outstanding track-record of delivering a portfolio in a highly regulated clinical setting.
- A diverse research program demonstrated by 10 or more journal and conference publications in prestigious venues (with at least 5 publications as a leading author). Examples include but are not limited to: NeurIPS, ICML, UAI, COLT, AAAI, KDD, ICLR, CVPR, ECCV, EMNLP, WWW, JMLR, Ann Stats, TIP, TASLP, TSP. Leadership in a high impact model deployment (e.g., developed over a period of 4+ years) or 4+ small-to-medium scale deployments.
- Is externally regarded as a world leading expert within the community

**Desirable for the role**
- 5+ years of experience within the pharmaceutical industry with extensive knowledge of clinical trial process (all phases) and associated regulatory activities.
- Deep understanding of drug development and clinical trial process and data (all phases).
- Participation and activity in the scientific community on program committees, editorial boards, organizing workshops, etc.
- Demonstrated leadership potential in research and capability in expanding the frontier of addressable problems.
- Demonstrated experience in at least five of the following research areas: foundational research in machine learning, statistical learning theory, deep learning, generative models, active learning and optimization, causality, natural language processing, graphs and structured data, audio and signal processing, computer vision.
- Track record of collaborating successfully with AI engineering teams to deliver complex machine learning models

**Why AstraZeneca?**

At AstraZeneca we’re dedicated to being an excellent Place to Work. Where you are empowered to push the boundaries of science and unleash your ambitious spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration, and always committed to lifelong learning, growth and development. We’re on an exciting journey to pioneer the future of healthcare.

**So, what’s next?**

Are you already imagining yourself joining our team? Are you ready to bring new insights and fresh thinking to the table? Good, because we can’t wait to hear from you.

DSAI #DataAI

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