Data Scientist, Machine Learning (Computational Biology)

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At GSK, we have bold ambitions for patients, aiming to positively impact the health of 2.5 billion people by the end of the decade. R&D is committed to discovering and delivering transformational vaccines and medicines to prevent and change the course of disease.

We believe the Greater Boston area is an important hub for the biotech and pharma industry, which is why we’ve invested in growing our footprint and expanding our R&D space in Cambridge, with a primary focus on additional state-of-the-art lab space. Here, we will bring together talent and expertise, building upon GSK’s long history of vaccine development, to create globally leading viral capabilities and cutting-edge vaccines technologies, as we add to our robust portfolio targeting infectious diseases at every stage of life.

In the plan to create a new hub for mRNA-based vaccine discovery in Cambridge, we are building new laboratories that will be focused on the development of state-of-the-art methods that will be supporting deep product understanding, process and product development, as well as testing of pre-clinical and clinical samples for new mRNA-based vaccines.

Are you interested in using advanced data science techniques to make significant contributions and global impact in viral vaccine development? We are looking for a highly skilled data scientist to join our dynamic and innovative Digital Virology team. In this key role, you will utilize your expertise in computational biology and machine learning to develop advanced models for vaccine and therapeutic applications. Collaborating with cross-functional teams, you will integrate experimental data with predictive algorithms to drive cutting-edge research.

Your contributions will be vital in advancing vaccine platform and enhancing our capacity to create next-generation vaccines and medicine. A strong foundation in computational biology, along with a proven ability to manage large-scale datasets and apply machine learning to solve biological challenges, is essential for success in this position.

Key Responsibilities:

• Design and implement predictive pipelines with a large-scale, heterogeneous datasets including genomic, proteomic, and epidemiological data.
• Data modeling and design innovative computational tools for vaccine candidate identification.
• Leverage advanced machine learning and algorithmic solutions for protein feature prediction and hypothesis generation.
• Identify, curate, and integrate relevant datasets and tools from public and proprietary sources to enrich computational design projects.
• Preparation and publication of scientific papers and congress reports.
• Foster computational innovation within Vx R&D and keep abreast of the new and most recent developments and innovations in the fields relevant for the role.

Basic Qualifications:

• PhD degree or a MS degree with at least 3 years of experiences in Bioinformatics, Computational Biology, Chemical Engineering, Data and Computer Science, Statistics, or other quantitative domains.
• Six months or more experience in a biological domain.
• One or more years of experience in algorithm development, machine learning and mathematical modeling techniques.
• Two or more years of experience in programming (Python, R, or C/C++) and experience using machine learning tools (e.g., TensorFlow, Pytorch, Scikit-Learn) and data analysis / visualization tools.
• Experience in predictive modeling, biological data processing and analysis or Mathematical modeling of high dimensional data.

Preferred Qualifications:

• Experience working in health care industry is a plus.

• Strong problem-solving and analytical skills, with the ability to propose creative and efficient solutions for complex challenges.
• Excellent written and verbal communication skills, capable of effectively conveying technical findings to stakeholders.

• Experience with deep learning techniques, including CNNs, RNNs, autoencoders, or transformers/large language models.
• Track record of using mathematical and computational principals to solve real world problems in fast-paced, cross-functional setting.
• Strong publication record in one of the following areas: bioinformatics and genomics, computational structural biology and molecular epidemiology, machine learning, or time-series modeling.
• Proficient with agile software development process.

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Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

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 organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).

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 place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.

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