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 Scientific Investigator Will Provide Key Technical Expertise Within The Scientific Computing Applications Group And Will Be Responsible For Design, Development, Implementation And Support Of Highly Scalable HPC Applications And Workflows Across All Of R&D. They Will Be Responsible For Proactively Addressing The Performance Issues Of Existing R&D Models By Optimizing For And Porting To High Performance Computing Resources That Will Be Leveraged To Accelerate The Timeline And Improve The Success Rate Of The Drug Discovery Process; Owning These Areas Based On Potential Impact; And Developing And Delivering Solutions In Collaboration With R&D Scientists. They Will Be Expected To Actively Seek, Learn And Deploy Cutting Edge Computational Simulation And Modelling Techniques And Methodologies. The Successful Candidate Will Require Hands-On Expertise In, Or A Strong Desire To Learn, High Performance Computing, Code And Workflow Optimization And Parallel Programming. Demonstrable Experience Developing And Tuning Scientific Applications Is Required. Experience Enabling Scientific Application Developers Working On R&D Projects Across A Wide Range Of Life Science Disciplines Would Be A Plus. Experience And Understanding At The Advanced Degree Level In Scientific Computing, 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 And Rapidly Engage, 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 Collaborate With Various Teams Working Closely With R&D Scientists To Rapidly Research, Develop And Implement Computational Modelling And Simulation Solutions To Expand And Accelerate Their Research. Knowledge Of Large Compute Clusters Including GPU And ASIC Based Systems, High-Speed Networking, Scientific Storage Solutions And The Ability To Develop And Optimize Scientific Software To Efficiently Utilize HPC Environments. Ability To Transform Scientific Computing Prototypes Into Large Scale Productized Solutions For R&D Under Able Guidance. A Desire To Learn How To Adapt 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 With Minimal Supervision. Demonstrate Proficiency With Major Programming Languages And Frameworks (Python, R, Perl, Fortran, C, C++, CUDA, MPI, OpenMP, Etc). Experience Using These On Large Scale HPC Projects Is A Plus. Ability To Translate Prototype Models In R, Python, Scala Etc Into Efficient Highly Scalable Models. Demonstrate Proficiency In Utilization Of Resource Management And Scheduling Systems, Primarily Slurm, Kubernetes Etc. Ability To Work On Multiple Projects With Competing Priorities. Bring Fresh Perspective On Approaches To Scientific Application Development In R&D With A Researcher-First Design Awareness. Preferred Qualifications: Direct (3+ Years) Experience In Scientific Computing, Algorithm And Software Development. Experience (3+ Years) Developing And Optimizing Scientific Models For World Class High Performance Computing Systems. Experience (2+ Years) Working With And Optimizing For Heterogeneous 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. Clearly Communicate Complex Computational Solutions And Application Performance-Related Issues To Non-Technical Scientists And Other Stakeholders Must Be Inquisitive, Creative, Bold And Extremely Energetic To Work In A Fast-Paced Rapidly Evolving Environment. Demonstrate Interpersonal Abilities To Work Flexibly In Matrixed Teams. 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. Duties And Responsibilities: Work With The Director Of Scientific Computing Applications To Best Implement Strategic Plans For On-Prem, Hybrid And Multi-Cloud Computational Resources To Support GSKs R&D Strategy Work With R&D Tech, Data Delivery And Scientific Analytics And Visualization Groups, As Directed, To Develop And Deploy Data Capture, Processing And Migration Systems That Ensure Efficient Connectivity And Portability Into Scientific And HPC Resources. Develop, Evaluate And Test New Methodologies In Line With The Strategic Vision Of Scientific Computing. Document And Catalog Problem Resolution Procedures For Effective User Enablement. Deploy And Evaluate Proof Of Concept HPC And Scientific Computing Solutions. Ensure The Needs And Requirements Of Individual Scientific Researchers Are Understood And Communicated Accordingly To Leadership For Prioritization. Work With The Scientific Compute Infrastructure Team In Capacity Planning Activities. Work With Scientists To Develop Solutions And Implement Efficient, Automated Workflows For Computational Problems. Provide Support When Needed To Ensure That The High-Performance Computing Applications Are Operating At Optimal Performance And Reliability Levels. Occasional Domestic And International Travel. Perform Other Job-Related Duties As Assigned.
