Experience Inc. Jobs

Req #: 224689

Department: OPHTHALMOLOGY

Posting Date: 03/14/2024

Closing Info: Open Until Filled

Salary: $3,667 - $6,000 per month

Shift: First Shift

Notes: As a UW employee, you will enjoy generous benefits and work/life programs. For a complete description of our benefits for this position, please visit our website, click here. (https://hr.uw.edu/wp-content/uploads/sites/3/2018/02/benefits-professional-staff-librarians-academic-staff-20230119_a11y.pdf) Please note that this position has been re-posted. If you have already submitted your application, you need not submit it again, as it has already been received.

As a UW employee, you have a unique opportunity to change lives on our campuses, in our state and around the world. UW employees offer their boundless energy, creative problem-solving skills and dedication to build stronger minds and a healthier world.

UW faculty and staff also enjoy outstanding benefits, professional growth opportunities and unique resources in an environment noted for diversity, intellectual excitement, artistic pursuits and natural beauty.

The University of Washington’s Department of Ophthalmology has an outstanding opportunity open for a Temporary Research Scientist 1.

The Lee Computational Ophthalmology Lab is leading collaborative efforts on large multidisciplinary research projects, using Big Data and machine learning, involving the relationship between the eye and brain. The Research Scientist/Engineer 1 will play a critical role in these important studies.

POSITION PURPOSE
Under close supervision, the Research Scientist will: 1) utilize various sources of large datasets such as retinal imaging data, US Census, Medicare Claims data, UK Biobank data for Big Data research in Ophthalmology; and 2) analyze various sources of Big Data datasets using traditional statistics and machine learning approaches.

The RS will work on data abstraction, coding for data manipulations and data cleaning, and running statistical analyses under supervision. A significant amount of time will be spent on cleaning and manipulating the data and developing/applying basic machine learning algorithms for data analysis.

The RS will participate in presentations and writing manuscripts and is expected to continue in the development of technical knowledge related to data science and machine learning, review the recent literature, and implement new techniques under supervision.

DUTIES AND RESPONSIBILITIES Analysis – 70%

• Processing, cleansing, and verifying the integrity of data used for analysis

• Advance data manipulation for machine learning analyses

• Apply basic machine learning techniques for data analyses

• Perform statistical analyses and develop traditional biostatistical models

• Review literature and recent advances in machine learning, data science, computer vision, and related research in ophthalmology

• Assisting in the study design and implementation of study protocols

• Modify data for training deep learning algorithms

• Collaborate with other team members to accomplish organizational goals and to learn new approaches and tasks

• Writing research manuscripts, reports, reviews and summaries Data Collection – 30%

• Creating, submitting and maintaining the IRB documentations

• Recruiting and consenting patients for studies

• Performing basic study procedures under supervision

• Extract various sources of Big Data such as the electronic medical record or imaging data MINIMUM REQUIREMENTS

• Bachelor's Degree in Biostatistics, Computer Science, or related field

• 1 year of work experience in a related field. Equivalent education/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license/certification/registration. ADDITIONAL REQUIREMENTS

• Previous experience in clinical research in any healthcare setting strongly preferred.

• Proficiency with Microsoft Office suite of programs including Word, PowerPoint and Excel

• Flexibility to learn new technologies, APIs, and SDKs by reading documentation.

• Great oral and written communication skills

• Must have strong determination and a logical and independent mind to complete each project

• Must have very strong organizational abilities and experience in team focused work environment with excellent written and oral communication and interpersonal skills

• Ability to multitask and participate in different projects

• Ability to solve well defined problems using accepted methods and techniques

• Must comply with NIH, Federal, state and University regulations on the safe and ethical use of animals and humans in research

• Perform related duties as required DESIRED QUALIFICATIONS

• Master’s or PhD in Biostatistics, Computer Science, or related field AND 1 year of work experience in a related field. (Equivalent education/experience can substitute for minimum qualifications except where prohibited by legal requirements such as license/certificate/registration.) CONDITIONS OF EMPLOYMENT

• Must pass WA state background check Application Process: The application process may include completion of a variety of online assessments to obtain additional information that will be used in the evaluation process. These assessments may include Work Authorization, Cover Letter and/or others. Any assessments that you need to complete will appear on your screen as soon as you select “Apply to this position”. Once you begin an assessment, it must be completed at that time; if you do not complete the assessment, you will be prompted to do so the next time you access your “My Jobs” page. If you select to take it later, it will appear on your "My Jobs" page to take when you are ready. Please note that your application will not be reviewed, and you will not be considered for this position until all required assessments have been completed.

University of Washington is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to, among other things, race, religion, color, national origin, sexual orientation, gender identity, sex, age, protected veteran or disabled status, or genetic information.