Overview
About the team
We are an Agile team that uses knowledge graphs and machine learning in collaboration with our scientists to help develop better drugs faster, choose the right treatment for a patient and run safer clinical trials. The team is a wide mix, including Software Engineers, Machine Learning Engineers, Data Scientists, Ontologists and Bioinformaticians. We are looking for a Machine Learning Engineer to be embedded within our team and become a core pillar of our work.
About the role
We are seeking a knowledgeable and passionate Machine Learning Engineer to join our team.
At the core of our work lies systems biology, it drives the design of our data products, our analytical pipeline and our machine learning approaches. In this role, you will play a crucial part in weaving together experimental data coming from multiple experimental modalities and our in-house knowledge graph to make the best out of modern machine learning developments for drug discovery.
As a Machine… Learning Engineer, you will have the freedom to unleash your creativity and leave a lasting impact by shaping our engineering and scientific strategies. Our supportive and encouraging environment will provide the necessary resources to thrive and excel in your work.
What you will do
Your focus will be to design and build innovative machine learning systems to support our scientists in the development of new drugs. A special emphasis will be given to graph-based techniques and other higher-order data structures and methodologies.
Objectives of this role:
• Collaborate closely with chemists, biologists and other scientists to design and implement computational strategies for analysing complex biological datasets, including genomics, proteomics and other omics data.
• Develop and apply machine learning algorithms and models to extract meaningful insights from large-scale biological datasets, identify patterns and predict outcomes.
• Implement data pre-processing, feature extraction and dimensionality reduction techniques to enhance the quality of input data for machine learning models.
• Contribute to the design and optimization of experiments, ensuring the collection of high-quality data for analysis.
• Create and maintain pipelines for data processing, analysis, and visualization, ensuring reproducibility and scalability.
• Stay up-to-date with the latest advancements in computational biology, machine learning, and related fields, and integrate innovative methods into our research projects.
• Collaborate with cross-functional teams to present findings, share methodologies and contribute to project discussions.
• Contribute to scientific publications, conference presentations and grant proposals.
What you’ll need:
• Ph.D. or Master’s degree in Computational Biology, Bioinformatics, Computer Science or a related field.
• Strong foundation in computational biology, genomics and molecular biology concepts.
• Proven expertise in machine learning techniques, including but not limited to deep learning, supervised and unsupervised learning, and feature selection.
• Proficiency in programming languages such as Python, R, and experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with processing and analysing large-scale biological datasets (e.g., next-generation sequencing data, single-cell data, proteomics data).
• Familiarity with data visualisation tools and techniques to effectively communicate results to both technical and non-technical stakeholders.
• Excellent problem-solving skills and the ability to think critically about experimental design and data interpretation.
• Strong communication skills and the ability to work collaboratively in a multidisciplinary team.
Bonus points:
• Publication record in relevant scientific journals or conference proceedings is a plus.
• Experience working with graphs, graph analytics and network science in general.
Company
AstraZeneca is a global, innovation-driven biopharmaceutical business that focuses on the discovery, development, and commercialization of prescription medicines for some of the world’s most serious diseases. But we’re more than one of the world’s leading pharmaceutical companies. At AstraZeneca, we’re proud to have a unique workplace culture that inspires innovation and collaboration. Here, employees are empowered to express diverse perspectives and are made to feel valued, energized and rewarded for their ideas and creativity.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements
Company:
10001239 – Associate Principal AI Engineer
Qualifications:
Language requirements:
Specific requirements:
Educational level:
Level of experience (years):
Senior (5+ years of experience)
How to apply:
Please mention NLP People as a source when applying
https://careers.astrazeneca.com/job/barcelona/machine-learning-engineer/7684/60515582832?utm_campaign=nlppeople&utm_source=nlppeople&utm_medium=organic
