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Job description

Site Name: London The Stanley Building
Posted Date: Apr 15 2024

At GSK we see a world in which advanced applications of machine learning and AI will allow us to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized drugs, driving better outcomes at reduced cost with fewer side effects. It is an ambitious vision that will require the development of products and solutions at the cutting edge of machine learning and AI. If that excites you, we'd love to chat.

The AI/ML Sequence Learning Team applies machine learning and AI methods to biological sequence (DNA, RNA, protein) data from large-scale human genetic, functional genomic and single cell experiments. Models operating directly on sequence data that can infer how variants alter protein/RNA abundance, structure and function have the potential to be transformative in drug discovery, empowering us to find new life saving medicines.

We are looking for a Senior AI/ML Engineer to help us make this vision a reality. Competitive candidates will have a track record in developing SOTA deep learning models for solving challenging real world scientific problems. You should be an outstanding scientist with in-depth knowledge in modern machine learning. You can convert vaguely described biological/drug discovery challenges into well-defined machine learning problem. You can independently execute and deliver full AI/ML driven solution from sourcing training data, design and implementing SOTA machine learning models, testing, benchmark and product driven research for model performance improvement, to shipping stable, tested, performant code and services in an agile environment.

The AI/ML team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career and development from day one.

In this role you will
  • Design and implement novel scientific approaches to uncover and explain key relationships within a multitude of biological data types.
  • Leverage data and insights to produce robust, explainable, and accurate predictions across a variety of key biological and clinical tasks.
  • Connect and collaborate with subject matter experts in biology, genomics, and medicine.
  • Identify opportunities to apply the latest advancements in Machine Learning and Artificial Intelligence to build, test, and validate predictive models.
  • Develop and embed automated processes for predictive model validation, deployment, and implementation.
  • Deploy your algorithms to production to identify actionable insights from large databases.

Why you?

Qualifications & Skills:

We are looking for professionals with these required skills to achieve our goals:
  • Graduate studies in Computer Science or Applied Math, undergraduate studies in Computer Science and relevant graduate studies in the life sciences with a focus on AI/ML techniques, or undergraduate studies in Computer Science and equivalent work history. Candidates with graduate studies in CS and biological sciences or equivalent work history will be highly competitive.
  • Highly experienced in developing deep learning models.
  • An outstanding scientist, machine learning engineer, and software engineer. Demonstrate expertise and depth in at least one area and breadth across your expertise.
  • Proficiency with standard deep learning algorithms and model architectures.
  • Familiarity with current deep learning literature and math of machine learning.
  • In depth knowledge in machine learning best practices, scalable training and deployment, model introspection and evaluation.
  • Advanced level in PyTorch, Tensorflow, or other deep learning frameworks.
  • Highly experienced/accomplished in software engineering with advanced skills in python and/or C++
  • Experience with devops stacks: version control, CI/CD, containerization, etc.
  • At least one peer reviewed publication.

Preferred Qualifications & Skills:

If you have the following characteristics, it would be a plus:
  • PhD in Machine Learning and peer reviewed publications in major AI conferences.
  • Knowledge in disease biology, molecular biology and biochemistry.
  • Experience with biological data (e.g., genomics, transcriptomics, epigenomics, proteomics).
  • Experience in design, development and deployment of commercial AI/ML software.
  • Track record of contributing to open-source projects.
  • Mentality of commit early and often, metrics before models, and shipping high quality production code.

Ready to embark on an exhilarating journey where your skills and passion can make a real difference? Apply now and be part of our team driving innovation at the intersection of AI and healthcare. Together, let's shape the future of medicine and transform lives for the better.

Closing Date for Applications: Monday 29th April 2024 (COB)

Please take a copy of the Job Description, as this will not be available post closure of the advert.
When applying for this role, please use the 'cover letter' of the online application or your CV to describe how you meet the competencies for this role, as outlined in the job requirements above. The information that you have provided in your cover letter and CV will be used to assess your application.

During the course of your application, you will be requested to complete voluntary information which will be used in monitoring the effectiveness of our equality and diversity policies. Your information will be treated as confidential and will not be used in any part of the selection process. If you require a reasonable adjustment to the application / selection process to enable you to demonstrate your ability to perform the job requirements, please contact 0808 234 4391. This will help us to understand any modifications we may need to make to support you throughout our selection process.

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Why Us?

GSK is a global biopharma company with a special purpose - to unite science, technology and talent to get ahead of disease together - so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns - as an organization where people can thrive. Getting ahead means preventing disease as well as treating it, and we aim to positively impact the health of 2.5 billion people by the end of 2030.

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it's also about making GSK a place where people can thrive. We want GSK to be a workplace where everyone can feel a sense of belonging and thrive as set out in our Equal and Inclusive Treatment of Employees policy. We're committed to being more proactive at all levels so that our workforce reflects the communities we work and hire in, and our GSK leadership reflects our GSK workforce.

As an Equal Opportunity Employer, we are open to all talent. In the US, we also adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to neurodiversity, race/ethnicity, colour, national origin, religion, gender, 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*(*US only).

We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.

Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us on [email protected] or 0808 234 4391.

Please note should your enquiry not relate to adjustments, we will not be able to support you through these channels. However, we have created a UK Recruitment FAQ guide. Click the link and scroll to the Careers Section where you will find answers to multiple questions we receive .

As you apply, we will ask you to share some personal information which is entirely voluntary. We want to have an opportunity to consider a diverse pool of qualified candidates and this information will assist us in meeting that objective and in understanding how well we are doing against our inclusion and diversity ambitions. We would really appreciate it if you could take a few moments to complete it. Rest assured, Hiring Managers do not have access to this information and we will treat your information confidentially.

Important notice to Employment businesses/ Agencies

GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site.

Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenses GSK incurs, on your behalf, in the event you are afforded an interview for employment. This capture of applicable transfers of value is necessary to ensure GSK's compliance to all federal and state US Transparency requirements. For more information, please visit GSK's Transparency Reporting For the Record site.
Industry
Biological, Chemical, Pharmaceutical Science
Job Sector
Information Technology
Job Position
Network Engineer
City/Town
London
Postal Code
N1C 4AG
Address
London N1C 4AG, UK
Post date
Closing date
Reference Number
393900

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