Associate Director, Machine Learning Data

hace 6 meses

Barcelona, España AstraZeneca A tiempo completo

**Associate Director, Machine Learning Data Scientist, Oncology Data Science**

**Location**:Barcelona, Spain

**Salary**:Competitive with excellent benefits

The Computational Biology** **group is growing in Barcelona, and we are looking for new team members to join us at different roles (Sr Scientist/ Associate Director).

AstraZeneca is a company that always follows the science and turns ideas into life changing medicines. Oncology Data Science plays a unique role in driving both discovery and translation through leading computational/data driven approaches to all aspects of the drug discovery process.

**What you’ll do**

The Computational Biology team is undergoing expansion to meet the strategic priorities of Oncology Data Science with the vision of building computational oncology programs to pro-actively drive basic science and generate translational portfolio insights across assets and cancer types in Oncology R&D.

The successful execution of this role will impact the wider AZ oncology community, and our patients through discovery of features of the tumour microenvironment, cell-cell interactions and the transcriptional/genomic features that govern response and resistance to perturbations. The outcome will contribute to advising drug combination and patient selection strategies, discovery of novel oncology targets and deepen our knowledge of tumour-immune co-evolution. To do this you will:

- Develop AI/ML computational strategies to define novel approaches for analysis of multimodal data. You will be part/lead of a matrixed team of highly qualified computational scientists and individually contribute to deliver integrated ML/AI predictive and explainable models using spatial, single cell, preclinical, ex-vivo and clinical multi’omic and phenotypic data.
- Partner closely with leaders across Oncology Data Science, Translational Medicine and Bioscience to establish a translational data science strategy based on use of ML/AI approaches to facilitates back-translation through discovery of novel targets and/or prediction of drug combinations based on tumour-intrinsic and -extrinsic molecular and cellular insights.
- Use your expertise in cancer biology/drug discovery to deliver actionable insights that impact the development of the next generation of cancer medicines.
- Form effective collaborations with industry and academic leaders in the field, to develop AZ’s IP and/or publish AZ’s work in high impact journals.

**Essential requirements for the role**
- Relevant PhD in applied ML/AI to cancer biology or computational/systems oncology.
- Associate Director Level: Experience in developing and using AI/ML methods and leading successful computational biology programs in an academic and/or industry setting.
- Senior Scientist Level: Experience in applied AI/ML methods and driving computational biology research projects analyzing, integrating and interpreting data from multiple 'omic platforms in an academic and/or industry setting.
- Proven expertise in one of more of areas of AI/ML such as Bayesian modelling, variational methods, multi-instance learning, auto encoders, generative AI, LLMs, ANNs, transfer learning, pretrained/foundation models.
- Deep knowledge of cancer genomics (including clonality, mutations, evolution) and algorithmic and statistical methods applicable to cancer genomics/proteomics and/or single cell biology.
- Highly attuned communication skills and experience of working in a matrix environment and coordinating efforts and responsibilities around cross-functional project goals.
- Ability to coordinate and pursue simultaneous projects and deliver to deadlines.
- R and/or Python programming expertise in a Unix environment making use of high-performance computing environments.

**Desirable requirements for the role**:

- Outstanding publication record.
- Experience in ML-based modelling of single cell and/or spatial omics data.
- Well connected to a wide network of bioinformatics and oncology communities.

If you know someone who would be a great fit, please share this posting with them.

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