Systems Engineer V: Algorithm Development

Job description

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 103,000 colleagues serve people in more than 160 countries.

JOB DESCRIPTION:

Abbott Diabetes Care, the fastest growing division in Abbott, has a new opening for a System Engineer: modeling & algorithm development. In this position you will be a key contributor to exciting R&D projects related to next generation product development for our FreeStyle Libre medical device.

We are looking for a candidate with strong scientific and technical skills, who will excel in a matrixed environment working with data scientists/analysts and software developers. This person could either be an engineer or a scientist, or ideally, a combination of both, with a background in mathematical modeling of dynamic systems, control synthesis or development of algorithms based on the understanding of the underlying dynamic systems, medical devices, and some experience with software development.  The candidate will utilize knowledge of biology, physiology, analytical techniques, mathematics, and data analysis in a highly collaborative and fast-paced environment.   The analysis results are expected to drive product development and clinical insights.

Primary Function:

Leads a cross functional team on a sub-project in the development of new products. Finds solutions to complex product development problems. Develops system level design documentation and requirements specification, working with marketing, engineering and other stakeholders. Participates in specialized functions such as algorithm development, user interface development, chemical process development or data analysis methodology.  Develops and follows specialized procedures in executing experiments, evaluation and documentation of results Develops working relationships with cross functional groups.

Major Responsibilities:

1. Perform product definition, system architecture, requirements writing, requirements management, requirements analysis, risk analysis, hazard analysis, product test and evaluation, System V & V, and/or design control documentation.

2. Optimizes design processes.

3. Design and conduct system level characterization/verification of complex systems; collect, organize, analyze, and document test results.  

4. Integrate analytical and performance related elements with software, hardware, and electronics system components.

5.Communicate effectively and participate on cross functional development teams with good negotiating skills to direct multi-disciplinary teams toward solutions.         

6. Responsible for utilizing and maintaining the effectiveness of the quality system.

7. Responsible for compliance with applicable Corporate and Divisional Policies and performing other duties as assigned by management.

Qualifications:

Bachelors degree in an engineering or scientific discipline.  Masters degree or PhD ideal.  8 yrs product development experience in Engineering or physical science. Experience credit for advanced degrees beyond BS (2 years for Masters; 4 years for Doctorate).  Solid knowledge in mathematical modeling of dynamic systems (e.g. nonlinear differential equation, state-space continuous & discrete time domain model, etc.), ideally in the area of glucoregulatory systems (e.g. Minimal model and others/variations by Sorensen, Hovorka, Dalla-Man, etc., including PK-PD models of oral hyperglycemic agents and injectables). Strong knowledge in empirical methods of system identification and/or algorithm synthesis, preferably in the area of glucoregulatory systems. Good knowledge of CAD tools such as Matlab or Python. Solid knowledge of general engineering/science principals and laboratory skills. Understanding of the electro-mechanical, software, mathematical, chemical or biochemical process operative in diagnostic systems. Knowledge of stochastic systems modeling and control theory desired.

Preferred Background:

1. Data science capabilities:

• Linear regression, model fitting / system identification, stochastic system modeling
• Data visualization

2. Experience reconciling first principles and empirical data (e/g/ clinical study data).

3. Matlab or Python software experience, or equivalent.

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