Site Name: Heidelberg - Office
Posted Date: Jun 7 2021
At GSK we see a world in which advanced applications of Machine Learning and AI will allow us to develop transformational medicines using the power of genetics, functional genomics and machine learning. AI will also play a role in how we diagnose and use medicines to enable everyone to do more feel better and live longer. It is an ambitious vision that will require the development of products at the cutting edge of Machine Learning and AI.
The opportunities for machine learning extend to many other areas of our business, including medicine safety, manufacturing and supply chain. To realize these opportunities, GSK has created a global Artificial Intelligence and Machine learning group (AI/ML), with locations in London, San Francisco, Boston, Philadelphia and Heidelberg, to focus on the development and application of machine learning to problems of critical importance at GSK. We possess a world-leading data and computational environment (including specialist hardware) to enable large-scale, scientific experiments that exploit GSK's unique access to data.
By actively engaging with the machine learning community and publishing our research, code and models built on public data, the AI/ML group operates at the cutting-edge of machine learning research. To help us, we seek up to 10 passionate , early-careers researchers who wish to turn their talents to healthcare, learn about the pharmaceutical industry and software engineering, and translate their research into tools that aid discovery and development of transformational medicines and vaccines. This fellowship is a two-year position with optional extension.
Working together with GSK scientists and partners from industry and academia, this exciting opportunity will allow you to develop cutting-edge, machine learning research and apply it to key business challenges facing the industry. You can choose from a portfolio of critical projects, collated from across our business, or develop a bespoke, relevant project that interests you.
You will have access to outstanding experts in biology, chemistry, (software) engineering, data science and machine learning; unrivalled data sources and GSK's state-of-the-art laboratory and compute infrastructure to help you develop and validate your machine learning research. You will foster links between industry and academia, publish your work and present at conferences. Your knowledge and curiosity will be stretched, and you will have the potential to impact the lives of people threatened by or living with diseases of the developed and developing world.
As a GSK.ai Fellow, we'd like you to be able to:
- Carry out high-quality, novel and publishable research in artificial intelligence and machine learning with the aim of developing methods and algorithms to extract patterns from complex and high-dimensional healthcare-related data
- Identify opportunities to apply the latest advancements in artificial intelligence and machine learning to healthcare challenges, addressing capability and efficiency gaps in emerging methodologies where necessary
- Implement your algorithms using Python, PyTorch (preferred), Tensorflow or other technology as required
- Lead the planning and direction of your research and prioritise goals
- Connect and collaborate with subject matter experts in biology, chemistry, engineering and medicine to ensure the applicability of your research
- Communicate technical concepts to staff and partners at all levels up to senior leader/stakeholder and across all relevant disciplines
- Establish and nurture relationships with world-class institutions
- Represent GSK externally to advance technical capability across the industry by publishing in high-impact journals and presenting at prestigious conferences
- A minimum of an MSc in machine learning, statistics, mathematics, computer science, physics or a related quantitative field
- Expert understanding of at least one programming language
- Experience of carrying out independent research
- A PhD in machine learning, statistics, mathematics, computer science, physics or a related quantitative field
- An expert understanding of a programming language such as Python
- Experience of developing and applying machine learning-based methodologies
- A creative mindset and the ability to identify parallels between different, perhaps unrelated, application domains
- Experience with at least one deep learning framework such as PyTorch, TensorFlow or Keras
- Excellent written and verbal communication skills
- The ability to work autonomously and collaboratively as part of a team
- The desire to teach and learn every day
- A history of publishing research in high-impact journals
Our values and expectations are 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:
- Operating at pace and agile decision-making - using evidence and applying judgement to balance pace, rigour and risk.
- Committed to delivering high quality results, overcoming challenges, focusing on what matters, execution.
- Continuously looking for opportunities to learn, build skills and share learning.
- Sustaining energy and well-being
- Building strong relationships and collaboration, honest and open conversations.
- Budgeting and cost-consciousness
If you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US).
GSK is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive equal consideration for employment without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class.
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