Lead AI/ML Engineer, Computational Structural Biology

Key Skills

Aartificial intelligence, Design, Leadership Skill, Machine learning techniques, Optimization, PyTorch, TensorFlow

Job Description

We are seeking a highly experienced skilled lead AI/ML engineer, computational structural biology to join our dynamic and innovative AI/ML team. You will work closely with cross-functional teams to build AI/ML model for target identification, AI-driven next generation vaccines design and drug discovery. Initially, you will develop innovative approach to track, analyze and predict rapidly evolution of human pathogen with the goal to guide and accelerate the vaccines and drug discovery by data-driven approach. The successful candidate will have a deep understanding AI/ML, structural biology, protein engineering and apply the knowledge to design the next generation vaccines and medicine.

Responsibility

• Design and develop infrastructure for infectious disease surveillance and real-time tracking system.
• Develop AI/ML model to predict the circulating human pathogen’s evolution and mutation effect.
• Develop computational approaches which will identify and provide insights into possible best AI solutions to optimize vaccines design.
• Analyze and interpret large biological datasets using machine-learning and/or statistical techniques to identify patterns, trends, and insights.
• Develop and apply computational structural biology, deep machine learning model to generate insights and better extract knowledge from high-dimensional molecular datasets.
• Collaborate with cross-functional teams, including molecular biologist, immunologist, bioinformatics, software engineers to plan, identify and develop AI solutions for target identification, lead selection and late-stage clinical study.
• Build advanced computational approach in molecular modelling, protein design, antibody design.
• Apply state-of-the-art data mining technologies and AI centric approach to process and analyze biological data.
• Identify relevant public datasets, method, and strategies to augment growing internal database of high-dimensional datasets to meet specific unmet disease research needs.
• Stay up to date with emerging science, technologies, and industry trends to identify opportunities for innovation and improvement in vaccines and oncology R&D with AI-driven approach.

Why You?

Basic Qualifications

• Bachelors in computer science, computer engineer, computational biology, bioinformatics.
• Experience in structural biology, including structural determination of proteins and/or modeling protein and RNA structures and interactions.
• Experience in antibody structure-function relationship using semi-rational and computational design approach.
• Experience in at least one major deep learning framework (PyTorch, TensorFlow).
• Experience applying predictive approaches to biological and chemistry data to direct discovery or decision-making.
• Experience with constructing, building and validating machine learning models.

Preferred Qualification

• PhD or Master's in computer science, computer engineer, computational biology, bioinformatics, with 5 years of post-doc experience (or MS in one of these fields with 8+ years of related experience) in structural based drug design and drug discovery.
• Experience with contemporary deep learning methods; preferably with demonstrated applications of models in the areas of active learning, generative machine learning, graph neural networks, geometric deep learning, or large language modeling.
• Excellent problem-solving and analytical skills, with the ability to propose creative and efficient solutions.
• Independent, self-motivated, innovative, and able to excel in a goal-oriented, multifaceted, and fast-moving team environment are required.
• Ability to clearly convey methods and results to provide information to engage in collaborative improvement of analytical approaches with leadership and the informatics team.
• Knowledge of deep sequencing, immune repertoires and bioinformatic tools/ methods. 
• Expertise in machine learning/probabilistic modeling and methods development for applications in biology (e.g., NGS, single-cell -omics etc.)
• Experience in developing or optimizing vaccine design platforms for infectious diseases, especially mRNA, viral vectors, and other advanced delivery platforms. 
• Interdisciplinary research experience with focus on employing molecular or cellular profiling technologies for elucidation of human disease in academic or biopharmaceutical research environments.
• Experience in antibody generation and optimization in an industrial setting.

Why GSK?

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 impact the health of 2.5 billion people around the world in the next 10 years. 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.