Research Scientist/Engineer 4 (Project/Temporary)

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 4.

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 4 will play a critical role in these important studies.

There will be tremendous opportunity to grow as part of a very productive team. Under the technical guidance of an experienced scientist, the Research Scientist will apply data mining techniques, perform statistical analysis, develop visualization techniques, and build automated tools that can assist with diagnosis, prognosis, and understanding of the pathophysiology of various ophthalmic diseases using machine learning.

The Research Scientist is expected to continue to develop their technical expertise and knowledge as it relates to data science, programming, machine learning, including reviewing recent literature, and implementing new techniques with limited supervision. The Research Scientist 4 is expected to take the lead on manuscript writing and assist with the preparation of grant proposals, and to develop independent research, if desired.


Responsibilities:

This is an advanced level research position. The Research Scientist is expected to demonstrate initiative and the ability to troubleshoot independently with limited supervision.

Scientific Research Activities: 100%

Data mining using state-of-the-art methods

Selecting features, building and optimizing classifiers using machine learning techniques

Extending the electronic medical record or imaging data with third party sources of information when needed

Enhancing data collection and extraction procedures to include information that is relevant for building analytic systems

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

Data munging tasks to reshape data for statistical analyses, data visualization, and machine learning

Doing ad-hoc analysis and presenting results in a clear manner

Performing statistical analyses with traditional and machine learning methods

Collaborate with other team members to accomplish organizational goals and to learn new approaches and tasks while working under limited supervision

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

Write scientific manuscripts for publication in peer-reviewed journals in collaboration with relevant investigators at the University of Washington and at other institutions, foreign and domestic.

Write, or contribute to, research manuscripts, reports, reviews and summaries

Data backup and basic computer hardware maintenance.

Requirements:

Master’s degree in Computer Science, Mathematics, Physics, Biostatistics or related field AND at least four years 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.)

Excellent scripting and programming skills including: Java, SQL, Python, Torch, Lua, Linux

Experience working in headless server environments

Desire to learn novel computational techniques and understanding of scaling processes

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

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

Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.

Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable

Excellent applied statistics skills, such as distributions, statistical testing, regression, etc.

Excellent oral and written communication skills, including presenting data and results at meetings

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

Must have very strong organizational abilities and experience in a team-focused work environment with strong interpersonal skills

Comfortable leading multiple projects from start to finish

Ability to multitask, plan, 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:

PhD degree in Computer Science, Mathematics, Physics, Biostatistics or related field AND at least four years of work experience in a related field OR five years of experience working in computer science. (Equivalent education/experience can substitute for minimum qualifications except where prohibited by legal requirements such as license/certificate/registration.)

Application Process:

The application process for UW positions 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.