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Assistant Professor in Data Analytics

2 weeks ago

Ajman, Ajman, United Arab Emirates AJMAN UNIVERSITY Full time
Roles and responsibilities
  • A Ph.D. in Data Science/Analytics or related fields from an internationally reputableuniversity
  • Outstanding research record in thefield of data science, which is demonstrated by publishing in topinternational journals and conferences (Scopus andSCIE)
  • Strong assurance of distinction inteaching, curriculum development, and learning outcomeassessment
  • Experience in teaching data scienceand computing courses at the undergraduatelevel
  • Demonstrated ability to collaborateeffectively with colleagues in performing professionalservice.
  • Ability to communicate effectively inEnglish
  • Excellent interpersonalskills.
  • Industrial Experience in providingstatistical consultancy to researchers and thepublic
  • Open to cross-disciplinary cooperationin research, teaching

Essential Duties AndResponsibilities

The selectedapplicant will be expected to:

  • Develop and teach undergraduate inData Science/ Analytics and ComputerScience.
  • Engage in innovative andtechnology-based approaches to learning andteaching.
  • Publish high-quality research inleading internationally recognized journals in his/ her ownfield.
  • Participate in committees at thedepartmental, college, and/or university levels asassigned.
  • Actively engage in promoting thegrowth of the Ajman University.
  • Ability toprovide consultancy services to researchers and the businesscommunity.
  • Actively seek out methods,procedures, and resources to best achieve course and lessonobjectives.
  • Perform miscellaneous job-relatedduties as assigned

ApplicationProcess

A completed applicationwill include:

  • A letter ofinterest addressing qualifications for theposition.
  • A current curriculumvitae.
  • A statement of teaching philosophy andresearch.
  • Copies of transcripts of all graduatecoursework.
Desired candidate profile

1.Teaching andInstruction

  • CourseDevelopment and Teaching : Designing and teachingundergraduate and graduate-level courses related to data analytics,such as statistical analysis, data mining, machine learning, datavisualization, big data technologies, and predictive analytics. Thecourses may also cover specific tools such as Python, R, SQL,Hadoop, and Tableau.
  • Lectures andClassroom Management : Delivering lectures, seminars,and workshops, making complex data analytics topics accessible andengaging. Encouraging active student participation and fostering alearning environment that promotes critical thinking and hands-onpractice with data analyticstools.
  • Lab Supervision andProjects : Overseeing lab sessions where studentsapply analytical techniques to real-world datasets. Supervisingstudent projects that involve gathering, cleaning, analyzing, andinterpreting data to solve business or scientificproblems.
  • Mentoring GraduateStudents : Supervising graduate students working ontheses, dissertations, or research projects. Guiding studentsthrough the process of data collection, analysis, interpretation,and presentation of results.

2.Research and ScholarlyActivity

  • ConductingResearch : Engaging in original research in the fieldof data analytics. This could involve the development of newalgorithms, tools, or methodologies for analyzing data, as well asexploring new applications for data analytics in fields such ashealthcare, finance, business, or socialsciences.
  • ResearchCollaboration : Collaborating with faculty members,industry partners, and other researchers to conductinterdisciplinary research that uses data analytics to addresscomplex problems. Building partnerships with companies or researchinstitutions for data-drivenprojects.
  • PublishingResearch : Writing and publishing research findingsin reputable, peer-reviewed journals, conferences, or books.Establishing a strong research profile that contributes to theadvancement of the data analyticsfield.
  • GrantWriting : Applying for research funding fromgovernment agencies, industry partners, and private foundations tosupport ongoing research initiatives in dataanalytics.
  • Data-DrivenSolutions : Exploring real-world applications of dataanalytics, including developing models that predict trends,optimize processes, or improve decision-making in differentindustries (e.g., healthcare analytics, financial forecasting, orsupply chain optimization).

3.Professional Development and IndustryEngagement

  • StayingUpdated with Industry Trends : Keeping up with thelatest trends, tools, and technologies in data analytics, such asemerging machine learning algorithms, deep learning, andadvancements in big data analytics and artificial intelligence(AI).
  • IndustryCollaboration : Partnering with companies,non-profits, or government agencies to apply data analytics toreal-world problems. Offering consulting services or working onindustry-sponsored researchprojects.
  • ProfessionalNetworking : Attending and presenting at academic andindustry conferences, contributing to workshops, and networkingwith peers in the data science and analyticscommunities.
  • ContinuingEducation : Participating in professional developmentactivities, such as attending workshops, webinars, or certificationprograms, to keep skills current and contribute to thoughtleadership in the field.

4.Service to the Institution and AcademicCommunity

  • CommitteeWork : Serving on academic committees, such ascurriculum development committees, research committees, and studentevaluation committees. Contributing to the overall governance andstrategic direction of the department orcollege.
  • PeerReview : Participating in peer review for academicjournals and conferences, reviewing research papers and proposalsin the field of dataanalytics.
  • AdvisingStudents : Advising students on academic and careermatters, guiding them in choosing research topics, internships, andcareer paths in data science andanalytics.

5.Leadership and AdministrativeRoles

  • CurriculumDevelopment : Helping develop and review the dataanalytics curriculum to ensure that it reflects the latest trendsin the field and meets the needs of both students andindustry.
  • ResearchLeadership : Taking a leadership role in organizingresearch projects or collaborating with other departments orresearch centers within the institution. Mentoring junior facultyor new researchers in thefield.
  • StudentRecruitment : Participating in recruitment efforts bypromoting the data analytics program to prospective students.Assisting in the selection of graduate students for admission intothe program.
Key Skills
Data Quality,Education,DataAnalytics
Employment Type : Full-time
Department / Functional Area: Data Analysis
Experience: years
Gender: Male
Vacancy: 1