美国马萨诸塞大学洛厄尔分校博士后职位—自然语言处理与数据科学

美国马萨诸塞大学洛厄尔分校博士后职位—自然语言处理与数据科学

马萨诸塞大学洛厄尔分校（University of Massachusetts, Lowell，简称UMass Lowell）是一所美国国家级公立研究型大学，坐落于马萨诸塞州的洛厄尔（Lowell）市，并在马萨诸塞州的黑弗里尔（Haverhill）市拥有一座小型卫星校园。主校区位于波士顿以北25英里（40公里），横跨梅里马克河（Merrimack River）两岸。

被卡内基教学促进基金会分类为高研究活跃度（High Research Activity）大学。

Research Scientist (Ph.D.) in Natural Language Processing and Data Science

University of Massachusetts Lowell

Job Description

We are seeking a highly motivated research scientist in Natural Language Processing and Data Science to work with a team of MS, PhD students, staff, epidemiologists, biostatisticians, informaticians and computer scientists (https://bio-nlp.org/). The successful candidate will work on cutting-edge research projects related to natural language processing and data science, including but not limited to machine learning, deep learning, text mining, and knowledge representation, and to work on large longitudinal electronic health records.

Minimum Qualifications (Required):

-PhD in Computer Science, Data Science, Natural Language Processing, or a related field

-Strong research background in natural language processing and data science, with a focus on machine learning, deep learning, text mining, and knowledge representation

-Experience in developing and implementing algorithms for text analysis, classification, and information extraction

-Record of publications in top-tier conferences and journals

-Excellent programming skills in Python or another relevant language

Additional Considerations:

-Performs other job duties as assigned

Preferred Qualifications:

-Ability to work independently and as part of a team

-Excellent communication and collaboration skills

Special Instructions to Applicants:

Only current UML Employees within the Grants & Contracts (MTA/GRACE) bargaining unit will be considered during the first 10 business days of the posting. All other candidates will be considered after that period.

This is a Grants & Contracts (MTA/GRACE) bargaining unit position, Grade P16.

Review of applications will begin immediately and continue until the position is filled; however, the posting may close when an adequate number of qualified applications is received.

This position is contingent upon funding. The initial appointment will be for approximately one-year with a possibility of renewal based on productivity, successful performance and the availability of funding.

Please include a resume and cover letter with your application. Names and contact information of three references will be required during the application process.

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