Professor of Computer Science in MS in Machine Learning Program

Who We Are

Milwaukee School of Engineering (MSOE) is an academic institution intrinsically tied to the real world-a confluence of industry knowledge, work ethic and an enduring desire to know more.

The university offers bachelor's and master's degrees in engineering, computer science, machine learning, user experience, construction management, actuarial science, business and nursing.

With about 3,000 students, faculty and staff, MSOE is large enough for big opportunities and small enough for personal attention.

A Small University Dedicated to Achieving Big Things

MSOE is a supportive environment where everyone is valued. Our method of learning by doing is our distinction : it is how we teach, how we learn and how we serve.

Faculty bring their real-world experience into the classroom, and small class sizes keep instructors in close contact with students.

MSOE's top priority is serving our students. By joining our community, you are building the leaders of tomorrow.

Our Mission

MSOE is the university of choice for those seeking an inclusive community of experiential learners driven to solve the complex challenges of today and tomorrow.

We are united by our six values-collaboration, excellence, inclusion, innovation, integrity and stewardship-which represent the core of our campus culture.

Under the leadership of Dr. John Walz, MSOE has embarked on an ambitious strategic plan, Extraordinary Together , that propels the institution forward.

MSOE fosters a welcoming and inclusive environment where diversity, equity, inclusion and belonging (DEIB) are central to all campus initiatives and guided by our DEIB Strategic Plan .

The Electrical Engineering and Computer Science (EECS) department at the Milwaukee School of Engineering (MSOE) seeks applicants to fill one or more Computer Science Faculty positions at any rank to support a cutting-edge online Master's program in Machine Learning.

This candidate may also teach courses in our undergraduate Computer Science or Software Engineering programs and advise capstone and research projects.

Minimum Qualifications

• Candidates with expertise in Applied Machine Learning, Adversarial Machine Learning, Deep Learning, Generative AI, Tiny ML, Data Science, AI Platform Software, Data Engineering, or Cloud Computing are highly encouraged to apply, though expertise in any domain will be considered.
• Must have proficiency in oral and written communication
• Must have a Doctorate by the beginning date of the appointment (Fall 2024).
• Industry experience is highly valued by the EECS department, and experience in synchronous online instruction is preferred but not necessary.

The vision of the EECS Department at MSOE is to be recognized for encouraging and supporting all our students to achieve their full potential.

We expect and reward a strong primary commitment to excellence in teaching. All faculty, and especially junior faculty in EECS are supported through established mentoring and collaborative pedagogical development.

Faculty share course development materials and coordinate efforts to leverage shared expertise and perspectives to optimize the learning experience for students.

The EECS Department also values a broad range of scholarly activities including applied industrial, academic, and computer science education research.

Support for faculty in these various forms of research is facilitated through existing industrial partnerships, the MSOE Applied Technology Center, Clinical and Translational Science Institute (CTSI) and traditional funding agencies.

Significant investments have been made to support MSOE's academic mission including the construction of the $34M Dwight and Dian Diercks Computational Science Hall that houses the computing programs.

Diercks Hall is also home to Rosie, MSOE's supercomputer, which is an GPU-accelerated AI supercomputer with two NVIDIA DGX H100 servers, three NVIDIA DGX-1s, and 20 servers each with four NVIDIA T4 GPUs.

The nodes are joined together by Mellanox networking fabric and share 300 TB of network-attached storage.

How to Apply

• The review of applications will begin as they are received and continue until the position is filled. When applying, please upload a single PDF file under the "Resume Upload" section which includes : 1) a cover letter;
• 2) a curriculum vitae; 3) a teaching statement; 4) areas of teaching interest; 5) if available, evidence of successful teaching;

and 6) contact information for three references.

Why Join MSOE?

At MSOE, we invest in our employees' professional and personal growth. MSOE offers very competitive, fully comprehensive benefit plans to all full-time employees including medical, dental, life, disability and vision insurance as well as a 403(b) retirement plan with company matching of up to 6% of employee earnings and immediate vesting.

Educational benefits are available for employees and family members. Plus, employees have access to our state-of-the-art fitness center as well as on-site dining facilities.

MSOE also offers paid parental leave for employees. Located in the heart of downtown Milwaukee, MSOE is just blocks away from beautiful lakefront, the theater district, museums, sports and music venues, parks and shopping.

To view more detailed information about MSOE, please visit www.msoe.edu / hr .

The above statements reflect the general details necessary to describe the principle functions of the occupation described and shall not be construed as a detailed description of all the work requirements that may be inherent in the occupation.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

It is the policy of MSOE to provide equal employment opportunity to all individuals regardless of their race, ethnicity, color, creed, religion, sex, age, national origin, physical or mental disability, military and veteran status, sexual orientation, gender identity, genetic characteristics, marital status or any other characteristic protected by local, state or federal law.

This policy applies to all jobs at the University and to all the terms, benefits, and conditions of employment / enrollment.

Job Code : 111