Scripps Staff Scientist 

The position of Scripps Staff Scientist is an advanced-level position.  The position requires the individual to perform many non-routine scientific procedures and a great deal of thought planning to resolve complex problems as they arise.  It is necessary for the individual to exercise judgement in developing methods, techniques and evaluating criteria to obtain results.  Must have the ability to plan, organize and provide direction on assigned projects. The individual works closely with research scientists in support of a variety of research programs to mine, design, develop, and maintain analysis of large, complex, and unstructured biological datasets using computer programming and advanced statistical methods. This requires proficiency in developing computational pipelines, implementing machine learning and statistical modeling approaches, and translating research questions into analytical frameworks.  This position also provides direct support to faculty and their research teams to accomplish their research and teaching missions by utilizing HiPerGator services optimally and efficiently, the primary university resource for research computing.  The position also provides on-site support at the UF Scripps campus in Jupiter, Florida for the development and operation of complex, high-performance, and data-intensive computing systems in support of advanced scientific, engineering, and scholarly research.

General Faculty and User Support

• Collaborate with Information Technology (IT) providers, central and distributed, to provide seamless access to resources.
• Design workflows to meet the research and teaching objectives of faculty and their groups in various scientific and scholarly domains, including but not limited to: simulations, gene sequencing, artificial intelligence and machine learning, image and text analysis, digital humanity, parallel computing with shared memory (threads and OpenMP), and distributed memory (MPI and CUDA).
• Provide in-depth consulting services for research groups and actively participate in their research projects to provide computing, programming, and data analytics support in areas mentioned above.
• Work in buildings where faculty and their labs are located to optimize the ability to communicate about complex problems and collaboratively build solutions.
• Create the installation processes and supervise the creation of tools for system and application software installation, configuration, modification, monitoring, testing, and tuning.
• Install, maintain, and support open-source and licensed software for Linux and for Windows on lab workstations to allow efficient use of HiPerGator services.
• Design new features for HiPerGator services, if needed, to support faculty research and work with UFIT Research Computing (RC) colleagues to implement and test these features and services.
• Provide technical support and/or advice on transitioning between local and HiPerGator resources.
• Build, configure, and test new applications and libraries for general use and for deployment in PUBAPPS webservers to provide outside access to data and applications developed and maintained by researchers for their research communities.
• Develops, modifies, and applies software, algorithms, and computational pipelines to omics and other biological datasets to address research hypotheses using best-practices methodology.

Operating System Maintenance and Optimization

• Identify and report observed defects to either the open-source community or the vendor software, whichever is appropriate, and assist with the resolution or workarounds for the reported defects.
• Work on integration with vendor software so the system is secure and operates smoothly.
• Develop infrastructure to support database, warehouse designs, and data architecture for large, multi-college projects.
• Design and prepare technical documentation of all procedures.

Technical Training & General Consulting

• Provide training, support, and consulting services to faculty, graduate students, postdocs, and research scientists.
• Develop correlating training materials, instruction guides, and other written materials as needed in collaboration with the training team in Research Computing.

Document procedures

• Contribute to documentation on the website, wiki, and Confluence spaces for procedures to build, configure, and use the applications and workflows developed for faculty that can be of general applicability.
• In conjunction with research scientists, designs and analyzes experiments and datasets. Develops mathematical and statistical models for integrating disparate data sources to enable comprehensive analysis.
• Stays current with advancements in computational biology, data science methodologies, and analytical tools through literature review, professional development, and participation in relevant scientific communities.
• Assists in analysis and interpretation of research results for publications and presentations, including quality control analysis, data interpretation, and visualization.

Commensurate with experience. 

Ph.D. and/or MD in an appropriate scientific discipline required. A minimum of 2 years postdoctoral experience.

• PhD degree in an appropriate area of specialization (e.g., computational biology, bioinformatics, biostatistics, computer science, biology, biochemistry, or related field).
• Building complex workflows, such as those common in gene sequencing and machine learning and use of workflow management systems such as Nextflow or Snakemake.
• Contemporary web application frameworks, deployment, and CI.
• Provide excellent service through professional and courteous interactions with internal and external stakeholders while meeting business needs.
• Can thrive in a fast-paced, customer-focused, critical production, support, and development environment.
• Ability to think critically and creatively, possess a high standard of integrity, and be motivated to incorporate best practices into the organizational structure.  
• Possess a minimum of 2 years of related bioinformatics and computational biology experience, with a strong background in biostatistics and experience analyzing large-scale biological datasets.
• Knowledge of and experience with data management, statistical analysis theories and techniques, and computational pipeline development.
• Proficiency in Unix/Linux, Bash, Python, R, bash, Perl, and in compiled languages FORTRAN and C/C++or related programming languages.
• Proficiency in parallel programming for shared memory (threads, OpenMP) and distributed memory (MPI, CUDA).
• Ability to effectively prioritize workload, manage multiple concurrent projects, and meet deadlines with minimal supervision.
• Excellent written and verbal communication skills with the ability to clearly convey complex computational methods and results to diverse scientific audiences.
• Evidence of productivity through publications in peer-reviewed journals from Ph.D. or postdoctoral work.
  Prior experience with computational modelling relevant to molecular medicine.

In order to be considered, you must upload your cover letter and resume.

Application must be submitted by 11:55 p.m. (ET) of the posting end date.

This is a time-limited position.