Director of Scientific Computing Applications Development
Organisation Name: GSK
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Job description Site Name: USA - Pennsylvania - Upper Providence Posted Date: Oct 28 2019 Details: GSKs Scientific Computing groups mission is to accelerate the path to successful medicines by ensuring that access to and ability to use computational resources is never a barrier to scientific research. The group is responsible for researching, developing and deploying state of the art computational resources and expertise across all GSK R&D sites worldwide. There is a specific focus on rapid development, scale up and deployment of computational technologies, including both hardware and software, for executing on GSKs broader R&D strategy. The Director of Scientific Computing Applications Development will be responsible for leading the Applications Group within Scientific Computing bringing world class expertise in high performance computing (HPC) to all of R&D. They will be responsible for identifying areas in R&D where high performance computing resources can be leveraged to accelerate the timeline and improve the success rate of the drug discovery process; prioritizing these areas based on potential impact; and developing and delivering solutions in collaboration with R&D scientists. This role will require close collaboration with business partners and stakeholders across all R&D disciplines to determine both current and future requirements and priorities. They will be expected to take a leadership role in ensuring that GSK remains at the cutting edge of computational simulation and modelling. The successful candidate will require world class hands-on expertise in high performance computing, code and workflow optimization and parallel programming. Extensive experience developing and tuning scientific applications on large scale systems and managing scientific application developers working on R&D projects across a wide range of life science disciplines is required. Expertise in scientific computing and a detailed understanding of computational simulation and modelling, both theory and practice, is essential. They will require a solution driven mindset and the ability to quickly understand complex scientific problems, marshal appropriate resources and rapidly architect, optimize and deploy solutions to satisfy continually evolving R&D requirements. Basic Qualifications: Advanced degree in mathematics, engineering, computational or life sciences. Ability to think outside the box, quickly developing, constructing and deploying efficient and scalable computational solutions within a rapidly evolving R&D environment. A broad understanding of the pharma R&D process and the ability to lead a team working closely with R&D scientists to rapidly research, develop and implement computational modelling and simulation solutions to expand and accelerate their research. Expert knowledge of large compute clusters including GPU and ASIC based systems, high-speed networking, parallel storage solutions and the ability to develop and optimize scientific software to efficiently utilize HPC environments. Demonstrated experience transforming scientific computing prototypes into large scale productized solutions for R&D. Experience researching and adapting academic prototypes and methods in computational simulation and modelling to develop resilient and scalable solutions that can be deployed in a commercial and fast paced R&D environment. Strong proficiency with major programming languages and frameworks (Python, R, Perl, Fortran, C, C++, CUDA, MPI, OpenMP, etc), and experience using these on large scale HPC projects. Ability to translate prototype models in R, Python, Scala etc into efficient highly scalable models. Expert in advanced utilization of resource management and scheduling systems, primarily slurm, kubernetes etc. Ability to work both independently and as the leader of a team to manage multiple projects, make time critical decisions and rapidly problem solve. Fresh perspective on approaches to scientific application development in R&D with a researcher-first design awareness. Preferred qualifications: Extensive (8+ years) direct experience in scientific computing, algorithm and software development. Extensive (8+ years) experience developing and optimizing scientific models for leadership class high performance computing systems. Experience (3+ years) managing a team of computational and application scientists. Experience (3+ years) working with and optimizing for heterogenous compute and data analytics environments encompassing on-prem, hybrid and multi-cloud systems. Ability to work effectively with multiple groups and diverse skill sets across all scientific domains. Skilled in clearly and concisely communicating complex computational solutions and application performance-related issues to non-technical scientists and other stakeholders Knowledge of pharmaceutical drug discovery and development. Aware of, but not constrained by todays approaches. A strong desire to research, develop and test new computational approaches. Inquisitive, creative and bold. Disruptive and innovative thinker that can deliver results. Ability to work and thrive in an extremely energetic, intellectual, fast-paced environment. Excellent interpersonal abilities, demonstrated inclusivity, flexibility and a history of both leadership and working collaboratively in a team environment. Comfortable with risk, willing to fail, learn from it, and move on. Not scared to propose novel, cost effective, out of the box solutions. Experience with the diverse pharmaceutical and computational chemistry software landscapes including software suites from Schrodinger, Chemical Computing Group, OpenEye as well as state of art artificial intelligence methodologies etc. Experience working with and supervising external contractors and consultants. Duties and Responsibilities: Work with the Global Head of Scientific Computing and the Director of Scientific Computing Infrastructure to best define the strategic plans for on-prem, hybrid and multi-cloud based computational resources to support GSKs R&D strategy. Act as liaison to R&D tech, Data Delivery and Scientific Analytics and Visualization groups to facilitate data capture, processing and migration with a focus on application connectivity and portability into scientific and HPC resources. Prioritize and triage projects based on agreed metrics including impact on the R&D pipeline. Corral additional resources as needed to meet business priorities. Lead efforts to ensure rapid and efficient processing of scientific instrument data on HPC resources where needed. For example processing of raw Cryo-EM microscope images, automated processing of results from gene sequencers etc. Lead a collaborative research plan to develop, evaluate and test new methodologies in line with R&D strategy. Lead the requirement gathering for scientific applications both from vendor and user perspectives for effective implementation. Manage and supervise resources to include project assignments, reviewing procedures and results, and provide application level guidance; maintain effective problem resolution procedures. Maintain a comprehensive knowledge of state-of-the-art computing techniques and frameworks to build scalable parallel architectures. Document as appropriate and provide advanced level training to computational and data scientists on efficient use of cutting edge computing resources. Work closely with the scientific community to understand BioPharma computing trends in the industry and academic circles. Work with scientists to develop solutions and implement scalable workflows for computational problems. Provide expertise when needed to ensure that the HPC applications are operating at optimal performance and reliability levels. Occasional domestic and international travel. Perform and delegate other job-related duties as assigned.
