Job Description

Payroll Title:
CMPTL AND DATA SCI RSCH SPEC 3
Department:
BIOENGINEERING
Hiring Salary Range
$63,400 - $85,000 / Year
Worksite:
Campus
Appointment Type:
Contract
Appointment Percent:
100%
Union:
Uncovered
Total Openings:
1
Work Schedule:
8 hrs/day, Mon-Fri

#117528 Cmptl and Data Sci Rsch Spec 3

Extended Deadline: Tue 8/9/2022

For the safety and well-being of the entire university community, the University of California requires, with few exceptions, that all students, faculty and staff be vaccinated against the COVID-19 virus and influenza before they will be allowed on campus or in a facility or office. For more information visit: Flu Vaccine Mandate / COVID Vaccine Policy

Job posting will remain open until a suitable candidate has been identified.

This is a 100% contract position for 12 months with the possibility of extending or conversion to career status based on department needs and funding.

DESCRIPTION

Applies skills as a seasoned, experienced IT research professional. Uses computational, computer science, data science, and CI software research and development principles, with relevant domain science knowledge where applicable, along with professional programming concepts for medium-sized projects or portions of larger projects. Develops and optimizes a variety of computational, data science, and CI research tools and components. Performs research on current and future HPC, data, and CI technologies, hardware and software projects. Works on algorithm development, optimization, programming, performance analysis and / or benchmarking assignments of moderate scope where the tasks involve knowledge of either domain / computer science research requirements and / or CI design / implementation requirements.

The candidate will engage in theoretical and computational efforts to facilitate the development of future generations of single-cell models that are computationally tractable and can predict the functional states of the cell under a wide range of stress conditions more accurately than existing constraint-based models. The candidate will apply skills and domain knowledge in data analytics, scientific computing, nonlinear dynamics, and differential geometry to (i) develop tools and techniques for dimension reduction and time-scale decomposition of single-cell kinetic models, (ii) formulate candidate pre-biotic metabolic networks and (iii) identify and optimize synthetic pathways for C1 carbon fixation in a variety of host strains using in silico strain-design techniques and single-cell models.

The successful candidate plans, designs, develops, modifies, debugs, deploys and evaluates complex high-performance computing (HPC) and data science software and technologies, working closely with the Principal Investigator (PI) and team to coordinate schedules and goals for data science research projects and develop computational procedures. Duties include developing mathematical models and efficient computational algorithms/tools, building and curating large-scale reaction databases for strain design, and training other researchers in pipelines and tools.

QUALIFICATIONS

  • Intermediate knowledge of HPC / data science / CI.

  • Advanced skills, and demonstrated experience associated with one or more of the following: HPC hardware and software power and performance analysis and research, design, modification, Implementation and deployment of HPC or data science or CI applications and tools.

  • Demonstrated ability to regularly interface with management.

  • Demonstrated ability to contribute research and technical content to grant proposals.

  • Demonstrated effective communication and interpersonal skills. Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and to external research and education audiences.

  • Strong familiarity with low- and high-level programming languages, such as C++, Python, MATLAB, and GAMS.

  • Proven skills and experience in independently resolving broad computing / data / CI problems using introductory and / or intermediate principles.

  • Self-motivated and works independently and as part of a team. Able to learn effectively and meet deadlines.

  • Thorough experience working in a complex computing / data / CI environment encompassing all or some of the following: HPC, data science infrastructure and tools / software, and diverse domain science application base.

  • Proven ability to successfully work on multiple concurrent projects.

  • Proven ability to understand research computing / data / CI needs, mapping use cases to requirements and how systems / software / infrastructure can support those needs and meet the requirements. Demonstrated ability to develop and implement such solutions.

  • Demonstrated broad experience in one or more of the following: optimizing, benchmarking, HPC performance and power modeling, analyzing hardware, software, and applications for HPC / data / CI.

  • Demonstrated experience and ability to collaborate effectively with all levels of staff; technical, students, faculty and administrators

  • 2-5 years of postdoctoral experience.

  • PhD in Bioengineering, Chemical Engineering, or related fields.

  • Familiarity with dimensionality reduction using advanced topics from abstract linear algebra and differential geometry.

  • Prior experience with theoretical analysis of carbon-fixation pathways.

  • In-depth knowledge of convex and global optimization theory (LP, MILP, QP, SDP, NLP, MINLP).

  • In-depth knowledge of nonlinear dynamical systems theory (stability, bifurcation, branch continuation).

  • Proven publication record in development and application of computational tools for nonlinear dynamic systems.

  • Proven publication record in computational systems biology with a focus on physiological models of biological networks, such as constraint-based models.

  • Proven publication record in applied mathematics, scientific computing, and optimization journals.

SPECIAL CONDITIONS

  • Must pass a background check.

Job offer is contingent on successful engagement in the UC COVID-19 Vaccination program (fully vaccinated with documented proof or approved exception/deferral).

To foster the best possible working and learning environment, UC San Diego strives to cultivate a rich and diverse environment, inclusive and supportive of all students, faculty, staff and visitors. For more information, please visit UC San Diego Principles of Community.

The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, age, protected veteran status, gender identity or sexual orientation. For the complete University of California nondiscrimination and affirmative action policy see: http://www-hr.ucsd.edu/saa/nondiscr.html

UC San Diego is a smoke and tobacco free environment. Please visit smokefree.ucsd.edu for more information.

Application Instructions

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