This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking an experienced Senior User Experience Researcher with a background in biomechanics (preferred) or kinesiology to join our Human Factors team. This is a unique opportunity for an entrepreneurial, highly driven person with a well-rounded skill set to join the Human Factors team, whose responsibilities extend beyond those of traditional Human Factors or Biomechanics professionals. The ideal person for this role will need to have not only a strong grasp of, and experience with, UX research, but also be flexible and a strategic thinker able to take on a variety of tasks, including project management and client lead development. You should be able to perform these tasks somewhat autonomously and with little need for guidance. - The Human Factors team performs a variety of studies related to product use-related health (including musculoskeletal strain), safety (including physical injury risk), usability, and user experience. - Methodologies include motion capture, biofidelic kinetic computer modeling and simulation, physiological data recording, or eye tracking. - You will help in operationalizing client needs as empirical research questions. - Design bespoke studies around those research questions. - Collect data from participants using a wealth of custom-tailored methodologies. - Analyze data in creative ways and translate the results back into actionable outcomes for our clients. - Your work may also entail working up litigation matters related to alleged physical injuries and, eventually, testifying as an expert witness in biomechanics. - Experiences will be varied and diverse, possibly spanning automotive, medical, pharma, consumer electronics, appliances, heavy machinery, child products, and extended reality products. Job Responsibilities - Study design, execution, data analysis, and report preparation. - Managing multiple concurrent projects. - Client-facing activities, such as client management and business development. - Possibly serving as a testifying expert in litigation. Qualifications - Ph.D. in Biomechanics (preferred), Kinesiology, Sports Science, or a related basic scientific psychology field preferred. - A minimum of two to four years of experience in industry and with managing client projects. - Alternatively, Master’s Degree in Biomechanics (preferred), Kinesiology, or Sports Science, plus minimum of ten years experience in industry. - Excellent oral and written communication skills. - Entrepreneurial drive and passion to succeed. - Proven track record of ownership of empirical research, from study inception to study design and execution to data analysis and interpretation. - Excellent inferential statistics and data analytic skills. - Experience with setup of motion capture (preferred) and/or IMU equipment and analysis of resulting data. - Experience with biofidelic kinetic computer modeling and simulation desired but not required. - Experience with physiological data recording (EMG, EKG) desired but not required. - Possible interest in potential litigation support and/or forensic work. Physical and Mental Job Qualifications - Ability to travel as needed, depending on project assignments. - Prolonged periods of sitting at a desk and working on a computer. Benefits - Flexible work environment allows employees to work remotely, when needed. - Flexible Time Off policy. - Medical, Dental, and Vision Insurance. - 401k Match. - Commuter Benefit. - A reasonable estimate of the salary range for this role is $120,000 - $160,000.

• Designs, implements, and maintains end‑to‑end MLOps pipelines for training, validation, deployment, and monitoring of ML and AI models used in cancer screening and precision oncology solutions. • Builds and operates scalable, secure ML infrastructure on cloud and container platforms (e.g., AWS/Azure/GCP, Docker, Kubernetes) to support batch and real‑time inference workloads. • Implements CI/CD workflows for ML (data, model, and code), including automated testing, packaging, and promotion of models across development, staging, and production environments. • Establishes and manages model and data versioning, experiment tracking, and lineage to ensure reproducibility, auditability, and effective model governance. • Develops and maintains monitoring, logging, and alerting for model performance, data quality, drift, and system health, defining and meeting SLOs/SLAs for critical ML services. • Collaborates with data scientists, bioinformatics and biostatistics partners, and software/platform engineering teams to translate experimental workflows into production‑grade services integrated into customer‑facing and internal applications. • Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork. • Support and comply with the company’s Quality Management System policies and procedures. • Maintain regular and reliable attendance. • Ability to act with an inclusion mindset and model these behaviors for the organization. • Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 90% of a typical working day. • Ability to travel 5% of working time away from work location, may include overnight/weekend travel.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Black Hawk College seeks an Adjunct/part-time instructor to teach online non-western art history courses for the Art Discipline. This position can be taught fully remote. - Courses may include ART 285 Survey of Asian Art and ART 286 Survey of Non-Western Art. - These courses are offered each semester and meet institutional non-western requirement for all transfer degrees. - Interested applicants should have experience in one or more areas of non-western art history and can teach social, historical, and philosophical contexts of artworks. Qualifications - ART HISTORY - M.A., M.F.A. or Ph.D. in Art History required. - Emphasis on Non-Western Art and studio art preferred. - Teaching experience in art appreciation and art history courses preferred. - Must possess demonstrated oral English proficiency for classroom instruction. Requirements - Faculty members are expected to encourage learning by preparing appropriate syllabi. - Develop lectures, discussions, and other presentations or activities to enhance the student’s educational experience. - Develop and execute appropriate methods of evaluating student performance. - Develop, secure, and maintain the equipment and other instructional materials essential to the presentation of the classroom material. - Other duties may be assigned as required. Benefits - Please upload a cover letter, resume/CV, and teaching philosophy. - Letter of recommendations may be included but not required. - Any instructor hired at Black Hawk College will be required to submit official transcripts at his/her own expense. - Transcripts, once submitted, become property of Black Hawk College.

• Design and operate ML platforms that support end-to-end workflows: data ingestion, feature engineering, training, evaluation, deployment, and monitoring. • Build and maintain CI/CD for ML (testing, packaging, versioning, reproducibility, automated rollbacks, approvals). • Implement MLOps best practices: model registry, experiment tracking, lineage, governance, and reproducible training environments. • Develop scalable training infrastructure (distributed training, GPU scheduling, cost controls, auto-scaling). • Create and maintain feature pipelines / feature stores, ensuring consistency between training and inference (training-serving skew prevention). • Establish model monitoring and observability: performance, drift, bias/fairness signals (where relevant), latency, throughput, and data quality. • Build and own end-to-end LLM delivery pipelines: prompt/versioning, retrieval, orchestration, evaluation, deployment, monitoring, and iterative improvement. • Create robust LLM evaluation harnesses (offline + online): golden datasets, automated regression testing, human-in-the-loop review workflows, and risk scoring. • Build cost controls: token/cost budgeting, caching strategies, autoscaling, and performance tuning. • Productionize ML Models on GCP using containers and orchestration (e.g., GKE, Cloud Run), and build CI/CD for ML/LLM systems with automated tests and safe rollouts. • Implement observability: tracing, metrics, logs, dashboards, alerting for model/system health (latency, token usage, error rates, retrieval quality, hallucination indicators, drift where relevant). • Design systems with security and privacy by default: IAM, least privilege, secrets management, audit logs, encryption, data retention, and PHI/PII handling. • Implement governance: model/prompt lineage, dataset provenance, evaluation traceability, and approval workflows aligned with healthcare compliance expectations. • Integrate guardrails: content filters, policy checks, prompt injection defenses, structured output validation, and fallback strategies.