Performance Science Research Fellow
Position Overview The Cleveland Browns are seeking a highly motivated Performance Science Research Fellow for a two-year fixed-term position focused on advancing how training load is quantified, analyzed, and reported in American football. This role is designed for early-career professionals with strong quantitative, sports science, or performance analytics backgrounds who are interested in applied research within a high-performance professional sport environment. The Performance Science Research Fellow will work closely with the Performance Science, Sports Medicine, and StrengthConditioning staff to develop and validate new methodologies for monitoring player workload, integrating multi-modal data sources, and supporting data-informed decision making related to training, recovery, and on-field performance. This position offers a unique opportunity to contribute to innovative problem solving in a professional football setting, while building a portfolio of applied research suitable for academic publication and professional advancement. The role is also eligible to apply for PhD opportunities with Cleveland Browns educational partners, which may provide access to reduced tuition or scholarship opportunities, subject to acceptance into partner programs and their respective requirements. Key Responsibilities Performance MonitoringTraining Load Quantification Design, implement, and refine methods for quantifying training load in American football players, integrating internal and external workload metrics. Support the development of positional- and role-specific workload profiles and benchmarks. Contribute to the development and maintenance of decision support systems that integrate data from multiple domains (e.g., strengthconditioning, performance testing, workload, medical/injury, and schedule context) to inform daily and long-term planning. Applied ResearchAnalytics Lead and/or support applied research projects focused on: + Training load quantification and modeling in American football. + Relationships between workload, performance, and injury risk. + Practice design and periodization strategies informed by data. Perform advanced statistical analysis and modeling (e.g., mixed models, time-series analysis, machine learning, simulation) to address performance-related questions. Assist with additional performance, research, and analytics duties as assigned, including ad hoc analyses and cross-departmental projects that support evidence-informed decision-making. TechnologyInnovation Evaluate existing and emerging technologies (e.g., wearables, tracking systems, neuromuscular assessment tools, computer vision) for their utility in capturing workload and performance-related data. Assist in designing and implementing validation and reliability studies for new hardware and software solutions. Collaborate with vendors, internal IT, and data infrastructure teams (where applicable) to support data integration, storage, and access. CollaborationCommunication Participate in interdisciplinary case discussions related to player management, integrating data-driven insights into holistic decision-making processes. Present findings and recommendations to technical and non-technical stakeholders in clear, concise formats (dashboards, slide decks, written briefs). OperationalField Support Assist with on-field and training facility data collection during practices, games, and workouts (e.g., ensuring tracking systems are functional, managing athlete devices, verifying data capture). Support daily and weekly data processing routines, including data cleaning, merging, and verification across multiple systems. Contribute to the continuous improvement of internal data pipelines, documentation, and standard operating procedures related to performance monitoring. Qualifications EducationProfessional Background Master's degree in Exercise Science, Biomechanics, Kinesiology, Sport Science, Data Science, Statistics, Engineering, or a closely related field required. Enrollment in, or strong interest in pursuing, a PhD in a related discipline preferred. Demonstrated experience in applied performance science, sports analytics, or related research (e.g., thesis, publications, or significant projects). TechnicalAnalytical Skills Proficiency with statistical, analytical, and data querying tools (e.g., R, Python, SQL, MATLAB, or similar). Experience working with large, multi-dimensional datasets (time-series, tracking data, force plate data, etc.). Familiarity with sports science technologies commonly used in elite sport, such as: + GPS, LIDAR and/or RFID player tracking systems (e.g., Zebra, Catapult). + Accelerometers/IMU's, dynamometers, force plates, optical tracking + Athlete management systems and data visualization platforms (e.g., Tableau, Power BI, R Shiny). Strong understanding of workload concepts (e.g., external load, internal load, acute/chronic ratios, density and distribution of load) and their application to team sports. InterpersonalProfessional Attributes Demonstrated ability to work collaboratively within an interdisciplinary high-performance team. High level of professionalism, integrity, and discretion when handling confidential player and organizational information. Ability to work a flexible schedule, including evenings, weekends, and travel as dictated by team activities and research needs. TermCompensation Contract Term: 2 years Year 1 Compensation: $45,000 Year 2 Compensation: $50,000 Professional Development: May be eligible to apply for PhD opportunities that may include access to reduced tuition or scholarship opportunities, subject to acceptance and program-specific criteria.