AI/ML Engineer - Knowledge Graph
- Philadelphia, PA
Site Name: UK - London - Brentford, USA - California - San Francisco, USA - Pennsylvania - Upper Providence, USA - Pennsylvania - Philadelphia
Posted Date: Jan 25 2021
At GlaxoSmithKline we have created a world-leading data and computational environment to enable large scale scientific experiments that exploit GSK's unique access to data. Our focus is on bringing data, analytics & science together into solutions for our scientists to develop medicines for patients. An important component of this effort is building a large-scale knowledge base where multimodal information from various structured and unstructured sources can be jointly explored and leveraged.
We are seeking to grow our team with brilliant and diverse contributors with technical ability. We are looking for machine learning and natural language processing experts who are excited by challenges in automated knowledge base construction, including information extraction, entity resolution, graph-based embedding/prediction, and search. This role will involve leveraging state-of-the-art models for these tasks, as well as developing new methods to derive actionable data for scientists. This is an exciting role that will stretch your knowledge and curiosity, offering the opportunity to learn new skills and work within a global community.
This is a hands-on position where you will be empowered to be creative, ambitious and bold, to solve novel R&D problems and have the potential to directly impact the lives of patients living with disease. We have impressive toolkits and world class data, and we are now looking for talented people to join us.
As a Machine Learning Engineer, we'd like you to be able to:
- Partner with our NLP team and various data / computing platform teams to construct a knowledge graph of biological, chemical, and medical concepts, representing scientific literature and internal / external experimental findings
- Implement cutting-edge algorithms for inferring likely connections in the knowledge graph for downstream experimental validation
- Design and implement a framework for evaluating the quality and downstream impact of different algorithms for inferring new relationships in the biomedical knowledge graph
- Devise systems for leveraging knowledge graph information within biomedical machine learning problems
Why You? Basic Qualifications:
- Masters Degree or PhD focused on knowledge representation, or similar practical experience in an industrial or research setting
- Experience using a programming language such as Python, including fundamental software engineering principles and NLP/machine learning design patterns.
- Experience with at least one Deep Learning framework such as TensorFlow, Keras, or PyTorch
- Refereed publications in premiere NLP, ML, and/or bioinformatics venues in one or more areas related to information extraction and/or knowledge representation.
- Excellent written and verbal communication skills
- Familiarity with biomedical terminology and ontologies (e.g. UMLS metathesaurus)
- Ability to work autonomously and collaboratively as part of a team to both teach and learn every day
Our values and expectationsare at the heart of everything we do and form an important part of our culture.
These include Patient focus, Transparency, Respect, Integrity along with Courage, Accountability, Development, and Teamwork. As GSK focuses on our values and expectations and a culture of innovation, performance, and trust, the successful candidate will demonstrate the following capabilities:
- Agile and distributed decision-making - using evidence and applying judgement to balance pace, rigour and risk.
- Managing individual and team performance.
- Committed to delivering high quality results, overcoming challenges, focusing on what matters, execution.
- Implementing change initiatives and leading change. Sustaining energy and well-being, building resilience in teams.
- Continuously looking for opportunities to learn, build skills and share learning both internally and externally.
- Developing people and building a talent pipeline.
- Translating strategy into action - a compelling narrative, motivating others, setting objectives and delegation.
- Building strong relationships and collaboration, managing trusted stakeholder relationships internally and externally.
- Budgeting and forecasting, commercial and financial acumen.
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