Job description

This role is no longer accepting applications.

As a community, the University of Rochester is defined by a deep commitment to Meliora - Ever Better. Embedded in that ideal are the values we share: equity, leadership, integrity, openness, respect, and accountability. Together, we will set the highest standards for how we treat each other to ensure our community is welcoming to all and is a place where all can thrive.

Job Location (Full Address):

160 Trustee Rd, Rochester, New York, United States of America, 14627

Opening:

Worker Subtype:

Temporary

Time Type:

Part time

Scheduled Weekly Hours:

Department:

220980 Electrical Engineering Engg

Work Shift:

UR - Day (United States of America)

Range:

UR URG 104 H

Compensation Range:

$19.04 - $26.63

The referenced pay range represents the minimum and maximum compensation for this job. Individual annual salaries/hourly rates will be set within the job's compensation range, and will be determined by considering factors including, but not limited to, market data, education, experience, qualifications, expertise of the individual, and internal equity considerations.

Responsibilities:

Performs advanced highly specialized technical research activities, frequently designing or creating new machine learning algorithms for speech processing. Interprets activities/problems and selects approaches. Plans and conducts experiments, designing or creating new techniques and procedures. Evaluates results and prepares reports.

ESSENTIAL FUNCTIONS

Designing, training and evaluating a multi-lingual real-time speech foundation model
Applying the trained foundation model for downstream application problems like real-time multi-lingual voice conversion
Communicating experimental results to the supervisor and lab mates on a regular basis
Drafting papers, reports, and presentations of research progress for dissemination
Other duties as assigned.

MINIMUM EDUCATION & EXPERIENCE

High School diploma or equivalent and 5 years of relevant experience required
Associate's degree preferred
M.S. in Electrical Engineering, Computer Science, Data Science, or Applied Math preferred
Research experience with designing and training deep neural networks for speech signals preferred.
Or equivalent combination of education and experience

KNOWLEDGE, SKILLS AND ABILITIES

Machine learning, signal processing, deep neural networks, Python programming, using GPU clusters, data visualization, data analysis, report drafting, presentation drafting preferred

The University of Rochester is committed to fostering, cultivating, and preserving an inclusive and welcoming culture to advance the University’s Mission to Learn, Discover, Heal, Create – and Make the World Ever Better. In support of our values and those of our society, the University is committed to not discriminating on the basis of age, color, disability, ethnicity, gender identity or expression, genetic information, marital status, military/veteran status, national origin, race, religion, creed, sex, sexual orientation, citizenship status, or any other characteristic protected by federal, state, or local law (Protected Characteristics). This commitment extends to non-discrimination in the administration of our policies, admissions, employment, access, and recruitment of candidates, for all persons consistent with our values and based on applicable law.

What applying to University of Rochester usually looks like

Based on publicly available information, candidates applying through workday to University of Rochester can typically expect an online application requiring a profile, resume upload, and completion of standardized questionnaires, which may include voluntary self-identification and eligibility questions. Given the wide range of roles, from clinical and healthcare positions to administrative, technical, and facilities-related jobs, screening criteria likely vary by department. Applicants may be asked to complete assessments or skills-based questions depending on the position. After submission, candidates can generally expect an automated confirmation, followed by review from recruiters or hiring managers. The process may include multiple stages, such as phone screening, panel discussions, or in-person interviews, though this can vary widely. Response times vary, and candidates are encouraged to monitor their Workday account and email for updates throughout the process.

Based on publicly available information. LandEarly does not verify interview process details.

Laboratory Technician III

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