Role Description The College of Business & Economics is seeking qualified adjunct faculty to teach graduate-level courses in Statistics, Business Analytics, Quantitative Methods, or related areas. These courses are offered online and include interactive one-hour virtual class sessions on Monday or Tuesday evenings at either 7:00 p.m. or 8:00 p.m. Eastern Time, as assigned. Faculty are also expected to integrate Christian biblical values into course discussions in ways that support thoughtful reflection, ethical decision-making, and applied leadership in professional contexts. In addition, adjunct faculty are expected to participate in a monthly one-hour virtual faculty meeting on Thursday evening at 7:00 p.m. Eastern Time to support program alignment, student success, assessment, and continuous improvement. The ideal candidate will bring strong academic preparation, professional experience, Christian faith, and a commitment to engaging graduate students in practical, applied learning. Courses may include topics such as: - Organizational behavior - Change management - Leadership - Organizational culture - Team dynamics - Organizational effectiveness Primary Responsibilities: - Teaching assigned graduate courses - Facilitating meaningful student engagement - Providing timely feedback - Assessing student learning - Maintaining regular communication with students - Aligning course delivery with program learning outcomes - Supporting the mission of the College of Business & Economics Qualifications - Graduate credential in organizational behavior, organizational change, management, leadership, or a closely related field - At least 18 graduate credit hours in the teaching discipline - Relevant professional experience in leadership, management, organizational development, consulting, human resources, or change management Requirements - A Ph.D. or terminal degree in organizational behavior, organizational leadership, management, organizational development, or a closely related field (preferred) - Prior graduate teaching experience, especially in online formats (preferred) Company Description Anderson University does not unlawfully discriminate on the basis of race, color, national or ethnic origin, sex, disability, age, religion, genetic information, veteran or military status, or any other basis on which the University is prohibited from discrimination under the local, state, or federal law, in its employment or in the provision of its services. As a Christian institution of higher education, Anderson University is entitled to certain religious accommodations under federal and state law, including Title IX of the Education Amendments Act and Title VII of the Civil Rights Act. For questions or concerns contact the Office of Human Resources at hr@andersonuniversity.edu .

Role Description CoStar Realty Information Inc. seeks a Senior Machine Learning Engineer. - Lead and manage the deployment and management of machine learning models across production systems. - Collaborate with machine learning engineers and data scientists to design and implement efficient and scalable machine learning pipelines, monitoring, and testing frameworks, and data management processes. - Work with software engineers to ensure the seamless integration of machine learning models into applications and services. - Develop and maintain efficient and scalable data management processes for large-scale machine learning datasets. - Collaborate with the Infrastructure team to ensure the reliability, scalability, and security of production systems. - Stay up-to-date with the latest trends and best practices in MLOps, machine learning, and data management. - Advocate for tools and technologies to accelerate research. - Distribute neural networking training across fleets of computer servers to leverage massive datasets. - Optimize machine learning inference on mobile devices. - Telecommuting permitted from anywhere in the U.S. Qualifications - Bachelor’s degree, or foreign equivalent, in Computer Science, Electrical Engineering, or a closely related field plus five years of experience in the job offered or a related occupation. Requirements - Python and C++ programming for developing complex computer vision applications and computational geometry algorithms, including experience with performance optimization and memory management for processing large 3D datasets. Expertise in scientific computing libraries such as NumPy and OpenCV for sophisticated data manipulation and algorithm implementation (3 years). - SLAM (Simultaneous Localization and Mapping) and Structure from Motion for camera pose tracking and 3D reconstruction. Experience in visual odometry, feature tracking, bundle adjustment, and loop closure detection. Experience implementing EKF-based SLAM solutions and familiarity with state-of-the-art SLAM approaches from research literature (2 years). - 3D Computer Vision and Volumetric Reconstruction, including 3D reconstruction techniques including TSDF (Truncated Signed Distance Function) volumetric fusion, depth data processing, and 3D mesh projection/stitching. Experience with multi-view geometry, camera calibration, and point cloud processing. Experience with specialized 3D vision libraries and implementing algorithms from computer vision conferences (CVPR/ECCV/ICCV) (2 years). - Depth Sensing and Processing: comprehensive experience with depth camera systems like Kinect or LIDAR, depth data infrastructure for mixed reality pipelines, and depth compression schemes. Hands-on experience with depth map filtering, fusion of multiple depth sources, and integration of depth data with RGB information for scene understanding (2 years). - Mixed Reality Systems for Digital Twins: advanced expertise in developing computer vision components from mixed reality applications with focus on digital twin creation and interaction. Experience with spatial mapping, environment understanding, camera tracking, surface detection, and 3D content placement in virtual environments that mirror physical spaces. Experience with integrating real-world geometry with virtual content for interactive digital twin applications (2 years). - Advanced Computer Vision Algorithms including camera calibration, pose estimation, feature extraction and matching, homography estimation, optical flow, and multi-view geometry. Experience implementing and optimizing these algorithms for specific application domains and hardware constraints (3 years). - Neural Radiance Fields (NeRF) and Novel View Synthesis for creating photorealistic 3D representations from 2D images. Hands-on experience implementing and optimizing NeRF variants for different applications and hardware environments (1 year). - Deep Learning for Computer Vision: specialized experience implementing and optimizing deep learning models for computer vision tasks such as object detection, semantic segmentation, depth estimation, and pose estimation. Experience with frameworks like PyTorch and adapting state-of-the-art architectures for specific computer vision challenges (2 years). - Embedded Computer Vision: Experience optimizing and deploying sophisticated computer vision algorithms on embedded systems with limited computational resources. Experience with ARM architectures, NVIDIA Jetson platforms (TX2), and techniques for efficient inference on edge devices. Experience implementing real-time vision systems on embedded hardware for applications such as smart cameras and mobile devices (2 years). - Multi-sensor Integration and 3D Environment Capture: Experience with multi-sensor systems for creating comprehensive 3D digital representations of physical spaces. Experience implementing sensor fusion algorithms, localization, mapping, and environment understanding for indoor and outdoor spaces. Experience developing systems that can perform real-time perception tasks in dynamic environments and create accurate 3D models from multiple data sources. Experience with multi-camera calibration, synchronization, and integration for creating seamless 3D spatial models (2 years). Benefits - EOE, including disability/vets. - Must be legally authorized to work in the U.S. without sponsorship. - CoStar Group is an Equal Employment Opportunity Employer; we maintain a drug-free workplace and perform pre-employment substance abuse testing.

Role Description The MEAL Global Coordinator serves as the Global Technical Advisor for Monitoring, Evaluation, Accountability and Learning (MEAL) and Data Management for the Global Initiative, sits in the GCU (JPRWEE Secretariat) and reports to the Global Coordinator. - Lead the enhancement, operationalization and positioning of a robust Joint Programme MEAL framework across all participating countries and globally. - Ensure rigorous evidence on economic empowerment is generated to drive strategic decision-making, learning, accountability and programme adjustment globally. - Provide direct strategic oversight to six country-level MEAL Coordinators, ensuring global MEAL system is mainstreamed at country level. - Collaborate closely with national teams and technical units across the Agencies at HQ level. Qualifications - Advanced University degree in international development, social sciences, statistics, development economics or related subject, or first University degree with additional years of related work experience and/or trainings/courses. - Over five years of professional experience in Monitoring & Evaluation and Results-Based Management, ideally in relation to food and nutrition security, livelihoods, gender equality and women’s economic empowerment. - At least 3 years in a coordination role at regional or global level. - Proven leadership in managing MEAL systems, applying a wide range of quantitative and qualitative tools, methods, and analytical approaches for evidence generation and programme performance tracking. - Strong experience in designing and managing qualitative research. - Demonstrated ability to coordinate across UN agencies and multi-stakeholder environments. Requirements - In-depth Knowledge of Theories of Change and logical frameworks. - Excellent command of both quantitative and qualitative data analysis methods. - Skills in training, mentoring and coaching. - Excellent communication and interpersonal skills. - Strong understanding of gender equality and women’s empowerment principles. - In-depth knowledge of nutrition, food security, livelihoods, and climate resilience measurements. Benefits - WFP is a 2020 Nobel Peace Prize Laureate. - WFP offers a highly inclusive, diverse, and multicultural working environment. - WFP invests in the personal & professional development of its employees through a range of training, accreditation, coaching, mentorship, and other programs. - A career path in WFP provides an exciting opportunity to work across various country, regional and global offices. - We offer an attractive compensation package.

• Own the client's recommendation system end-to-end: design, training, deployment, and monitoring • Build and mature ranking and retrieval models that process behavioral signals — clicks, opens, purchases — at consumer scale • Operate ML systems at hundreds of millions of events per day, with direct impact on client revenue • Make independent technical decisions and engage directly with client engineering leadership — no intermediaries