Machine Learning Engineer (1 Year Fixed Term, 2 Openings)

Machine Learning Engineer (1 Year Fixed Term, 2 Openings)

School of Medicine, Stanford, California, United States

New

Information Analytics

Post Date 6 days ago

Requisition # 109023

Stanford University is seeking a Research Data Analyst 1 on a 1 year fixed term to work with faculty and students in the development of data processing and analysis pipelines for large-scale experimental and theoretical neuroscience projects.

Working closely with Dr. Karl Deisseroth and a team of neuroscientists and computational researchers in the Deisseroth Lab, the Research Data Analyst will play a pivotal role in designing and implementing data processing and analysis pipelines for large experimental and theoretical projects that enhance neuroscience research. Research Data Analyst will help develop data analysis pipelines, verify and organize large data archives, and aid in the development of software tools for processing disparate data types and performing large-scale statistical analysis. The analyst will focus on creating high-fidelity analyses specifically for the Human Neural Circuitry (HNC) program, making critical decisions regarding analysis design, statistical decision making, and potentially also psychological task development. The objective is to produce robust data processing and analysis pipelines that facilitate the study of cortical network dynamics in decision-making, affective processing, and sensory processing, electrophysiological signatures of neuropsychiatric disorders, and next-generation neuromodulation techniques for therapeutic interventions.

Duties include:

· Collect, manage and clean datasets.

· Employ new and existing tools to interpret, analyze, and visualize multivariate relationships in data.

· Create databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data and reporting requirements.

· Use system reports and analyses to identify potentially problematic data, make corrections, and determine root cause for data problems from input errors or inadequate field edits, and suggest possible solutions.

· Develop reports, charts, graphs and tables for use by investigators and for publication and presentation.

· Analyze data processes in documentation.

· Collaborate with faculty and research staff on data collection and analysis methods.

· Provide documentation based on audit and reporting criteria to investigators and research staff.

· Communicate with government officials, grant agencies and industry representatives.

* - Other duties may also be assigned

The job duties listed are typical of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.

DESIRED QUALIFICATIONS:

• Possess a BS and/or MS in a STEM field with a computational component.

• Be comfortable manipulating data sets, particularly large timeseries ones.

• Be able to analyze and work with custom coding tools.

• Be proficient in Python.

• Have excellent organizational skills and attention to detail.

• Have strong verbal and written communication skills.

• Be able to work in a team setting.

EDUCATION & EXPERIENCE (REQUIRED):

Bachelor's degree or a combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.

KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):

· Substantial experience with MS Office and analytical programs.

· Strong writing and analytical skills.

· Ability to prioritize workload.

PHYSICAL REQUIREMENTS : *

· Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.

· Occasionally use a telephone.

· Rarely writing by hand.

* - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.

WORKING CONDITIONS:

Some work may be performed in a laboratory or field setting.

Onsite : This position is based on the Stanford main campus.

The expected pay range for this position is $80,148 to $99,773.

Stanford University provides pay ranges representing its good faith estimate of the salary or hourly wage the university reasonably expects to pay for a position upon hire. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location, and external market pay for comparable jobs.

At Stanford University, base pay represents only one aspect of the comprehensive rewards package.

WORK STANDARDS

· Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.

· Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.

Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide,

• • Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

Additional Information

• Schedule: Full-time

• Job Code: 4751

• Employee Status: Regular

• Grade: G

• Requisition ID: 109023

• Work Arrangement : On Site