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Professor Mining Engineering Jobs (NOW HIRING)

Professeur a temps-partiel regulier / Regular Part-Time Professor Date Posted (YYYY/MM/DD): 2026/05 ... mining platforms. * Knowledge of scripting or programming languages (e.g., Python, R, SQL)

... of Engineering Design and Teaching Innovation Course Title: Process Modelling, Mining, and ... Professeur a temps-partiel regulier / Regular Part-Time Professor Date Posted (YYYY/MM/DD): 2026/05 ...

Post Doc Res Assoc w/Ret

Campus, IL ยท On-site

$60K - $70K/yr

The successful candidate will contribute directly to the research and implementation of workflows for AI model identification, publication mining, metadata engineering, search and retrieval, and ...

The successful candidate will contribute directly to the research and implementation of workflows for AI model identification, publication mining, metadata engineering, search and retrieval, and ...

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Professor Mining Engineering information

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$22K

$85.1K

$176K

How much do professor mining engineering jobs pay per year?

As of Jun 27, 2026, the average yearly pay for professor mining engineering in the United States is $85,052.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,000.00 and $106,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Professor Mining Engineering position, and why are they important?

To thrive as a Professor of Mining Engineering, you need an advanced degree (typically a Ph.D.) in mining engineering or a related field, substantial research experience, and a solid background in teaching and curriculum development. Familiarity with mining simulation software, geological modeling tools, and relevant safety certifications such as MSHA are important technical assets. Excellent communication, mentoring, and organizational skills help engage students and foster a productive learning environment. These skills enable professors to effectively educate future engineers, advance research in the field, and maintain industry relevance.

What are the typical daily responsibilities of a Professor in Mining Engineering?

A Professor of Mining Engineering usually divides their time between teaching undergraduate and graduate courses, conducting cutting-edge research, and advising students on academic and career matters. Regular responsibilities include preparing lectures, developing lab sessions, securing research funding, supervising graduate theses or projects, and staying current with industry advancements. Professors often collaborate with industry partners, participate in academic committees, and may contribute to public outreach or international projects. This diverse workload offers a dynamic environment and the opportunity to shape the next generation of mining professionals.

What is a Professor of Mining Engineering job?

A Professor of Mining Engineering is an academic professional who teaches, conducts research, and mentors students in the field of mining engineering. They develop and deliver course materials on topics like mine design, mineral processing, and sustainable extraction methods. Additionally, they engage in research to advance mining technologies and collaborate with industry partners. Professors may also contribute to academic publications and secure research funding. Their role helps train future engineers while contributing to innovations in the mining sector.

More about Professor Mining Engineering jobs
What are the most commonly searched types of Professor Mining Engineering jobs? The most popular types of Professor Mining Engineering jobs are:

APTPUO-Winter 2027-MEM5300 B (online)

Uottawa

Campus, IL โ€ข On-site

$239.47/hr

Part-time

PTO

This job post hasย expired 1 day ago.ย Applications are no longer accepted.


Job description

Posting Reason:

New Position

Location:

Main Campus

Academic Period:

2027 Winter Semester

Faculty:

Faculte de genie / Faculty of Engineering

Academic Unit:

Ecole de conception et d'innovation pedagogique en genie \\ School of Engineering Design and Teaching Innovation

Course Title:

PRINCIPLES OF DATA ANALYTICS (On line)

Course Code:

MEM5300

Section:

B

Course Description:

Description: This course focuses on the application of data mining techniques and predictive analytics to business problem-solving. It covers key algorithms and techniques for extracting meaningful insights from business data, including data preprocessing, decision trees, neural networks, k-nearest neighbors, clustering, and association rules. Students will gain hands-on experience with data mining tools and software, applying these techniques in managerial contexts such as customer relationship management, marketing, sales, credit scoring, and churn analysis.

Posting limited to:

Professeur a temps-partiel regulier / Regular Part-Time Professor

Date Posted (YYYY/MM/DD):

2026/05/19

Applications must be received BEFORE (YYYY/MM/DD):

2026/06/20

Expected Enrolment:

40

Approval date:

2026/05/19

Number of credits:

3

Work Hours:

39

Hourly Rate:

Enseignement / Teaching: $239.47 (2024-2025)

The academic year starts on September 1 and ends on August 31.

These rates do not included vacation pay nor statutory pay.

These rates will be applied until a new collective agreement is ratified. Retro will be paid after the ratification.

Course type:

B

Posting type:

Regulier / Regular

Language of instruction:

Anglais | English

Competence in second language:

Active

Course Schedule:

Mardi | Tuesday 19:00-22:00 - -

Requirements:

  • Education: Bachelor's degree in Business, Computer Science, Engineering, or related field is required; Master's in Management or Engineering preferred. A Ph.D. is considered an asset.
  • Industry Experience: Demonstrated track record in professional or managerial roles involving data analytics, data mining, or technology-driven decision-making. Experience as a CTO or equivalent leadership role in a data-intensive or tech-focused organization is highly desirable.
  • Teaching Experience: Prior experience in post-secondary teaching or professional development instruction is preferred.

Technical and Analytical Skills

  • Proficient in data mining and predictive analytics, with the ability to teach both supervised and unsupervised learning techniques, including decision trees, neural networks, k-nearest neighbors, clustering, and association rules; familiarity with tools such as RapidMiner, WEKA, and others is a plus.
  • Extensive experience with IBM SPSS Modeler, including stream creation, model building and evaluation, and applying CRISP-DM within the visual interface.
  • Ability to apply analytical techniques to managerial contexts such as CRM, marketing, sales, credit scoring, and churn analysis.
  • Solid understanding of data preprocessing, including data cleaning, transformation, and partitioning.

Desirable Additional Skills

  • Familiarity with tools such as RapidMiner, WEKA, and other data mining platforms.
  • Knowledge of scripting or programming languages (e.g., Python, R, SQL)
  • Experience with integrating SPSS Modeler with business systems or databases.
  • Knowledge of modern data analytics trends and use of visual programming tools in business intelligence.

Additional Information and/or Comments:

An acceptable level of education and/or experience could be viewed as being equivalent to the educational required and/or demonstrated experience. If you are invited to continue the selection process, please notify us of any adaptive measures you might require. Information you send us will be handled respectfully and in complete confidence. Employees are required under provincial law to successfully complete all mandatory legislated training. The list of training may be modified by provincial law.

The hiring process will be governed by the current APTPUO collective agreements; you can click here for the main unit, here for the OLBI unit, or here for the Toronto/Windsor unit to find out more.

The University of Ottawa embraces diversity and inclusion in the workplace. We are passionate about our people and committed to employment equity. We foster a culture of respect, teamwork and inclusion, where collaboration, innovation, and creativity fuel our quest for research and teaching excellence. While all qualified persons are invited to apply, we welcome applications from qualified Indigenous persons, racialized persons, persons with disabilities, women and LGBTQIA2S+ persons. The University is committed to creating and maintaining an accessible, barrier-free work environment. The University is also committed to working with applicants with disabilities requesting accommodation during the recruitment, assessment and selection processes. Applicants with disabilities may contact vra.affairesprofessorales@uottawa.ca to communicate the accommodation need. All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.

Prior to May 1, 2022, the University required all students, faculty, staff, and visitors (including contractors) to be fully vaccinated against Covid-19 as defined in Policy 129 - Covid-19 Vaccination. This policy was suspended effective May 1, 2022 but may be reinstated at any point in the future depending on public health guidelines and the recommendations of experts.