Assistant Professor in Statistics
دوام كامل
في Ajman university
في
UAE
نُشرت يوم January 28, 2025
تفاصيل الوظيفة
Roles and responsibilities
1. Expertise in Statistical Theory and Methods- Foundational Knowledge : In-depth understanding of foundational topics in statistics, including probability theory, statistical inference, regression analysis, hypothesis testing, Bayesian statistics, and multivariate analysis.
- Advanced Statistical Techniques : Proficiency in advanced statistical methods such as time series analysis, categorical data analysis, machine learning, design of experiments, statistical modeling, and data mining.
- Statistical Software : Proficiency in statistical software and programming languages such as R, Python, SAS, STATA, MATLAB, and others for data analysis, simulation, and modeling.
- Mathematical Foundations : Strong background in the mathematical principles that underpin statistical theory, including calculus, linear algebra, real analysis, and measure theory.
- Course Development and Instruction : Designing and teaching undergraduate and graduate-level courses in statistics, such as introductory statistics, probability theory, regression analysis, statistical programming, and more specialized topics like data science or statistical learning.
- Active Learning : Implementing various teaching methods, including lectures, hands-on labs, group projects, and case studies, to engage students and enhance their understanding of statistical concepts.
- Student Assessment : Creating assignments, exams, and projects that assess students' understanding of statistical principles, as well as providing timely and constructive feedback.
- Mentoring and Advising : Advising undergraduate and graduate students on academic and career matters, helping them with course selections, research opportunities, and preparing for careers in statistics or related fields.
- Student Engagement : Creating a supportive learning environment that encourages student participation, critical thinking, and collaborative learning.
- Independent Research : Conducting high-quality research in areas of statistical theory, methodology, or application, and making original contributions to the field.
- Applied and Theoretical Research : Engaging in both theoretical research (e.g., developing new statistical methods or models) and applied research (e.g., applying statistical techniques to solve real-world problems in fields such as medicine, economics, engineering, or social sciences).
- Collaborative Research : Collaborating with faculty from other disciplines (e.g., data science, biology, economics, engineering) to apply statistical methods in interdisciplinary research projects.
- Publishing : Publishing research papers in reputable peer-reviewed journals, presenting findings at academic conferences, and contributing to the advancement of statistical knowledge.
- Research Funding : Writing and submitting grant proposals to secure research funding from government agencies, foundations, and industry partners.
- Collaborative Data Analysis : Collaborating with other researchers or departments to apply statistical methods in analyzing complex data sets, and assisting in the interpretation of results.
- Statistical Consulting : Providing statistical consulting services to researchers, organizations, or industry partners in need of expertise for data analysis, experimental design, or statistical modeling.
- Data Visualization : Developing effective ways to communicate complex statistical results to a non-technical audience through visualizations, reports, and presentations.
- Graduate Research Supervision : Supervising Master's and Ph.D. students in their thesis or dissertation research, guiding them through the development of their research questions, data collection, statistical modeling, and analysis.
- Dissertation Advising : Providing ongoing mentorship and feedback to graduate students to help them succeed in their academic and professional goals, including preparing them for publishing research and academic job searches.
- Student Research Projects : Encouraging and mentoring students in independent research projects, fostering a collaborative and supportive research environment.
- Staying Current with Advances in Statistics : Continuously updating knowledge and skills by reading the latest research papers, attending conferences, and participating in professional development activities related to statistics and data science.
- Teaching Innovations : Experimenting with innovative teaching methods, such as flipped classrooms, online teaching platforms, or interactive statistical software to enhance student learning.
- Industry Trends : Staying informed about trends in data science, machine learning, and big data analytics, and incorporating these emerging topics into teaching and research.
Desired candidate profile
- Graduate with a MSc. from a reputable university.
- The applicant must have at least (3) years experience in teaching in an academic institution applying the credit hours system.
- Develop and deliver courses to students in specified discipline areas of study, considering and aiming to achieve the fundamental standards of the University.
- Evaluate and monitor individual student progress and provide feedback to sustain student success.
- Actively seek out methods, procedures and resources to best achieve course objectives.
- Collaborates and supports colleagues regarding research interests and co-curricular activities.
- Perform miscellaneous job-related duties as assigned.
- Excellent oral and written communication skills in English (Arabic is a plus).
- Excellent in developing and delivering presentation.
- Excellent in creating, composing and editing written materials.
- Strong interpersonal and organizational skills.
- Knowledge of computerized student information systems.
- Program planning and implementation skills.
- Only short-listed candidates will be contacted
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