Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may:  - Design original computational mathematics problems that simulate real mathematical research workflows; - Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy); - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); - Develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis; - Base problems on real research challenges or practical applications from mathematical practice; - Verify solutions using Python with standard mathematical libraries; - Document problem statements clearly and provide verified correct answers. What we look for This opportunity is a good fit for mathematicians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - Degree in Mathematics (Pure or Applied) or related fields; - Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; - 2+ years of professional experience: applied, research, or teaching experience is applicable; - Experience with numerical methods and symbolic computation; - Ability to design problems that mirror real mathematical research workflows; - Familiarity with computational complexity theory; - Strong written English (C1+). How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $76 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may:  - Design original computational mathematics problems that simulate real mathematical research workflows; - Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy); - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); - Develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis; - Base problems on real research challenges or practical applications from mathematical practice; - Verify solutions using Python with standard mathematical libraries; - Document problem statements clearly and provide verified correct answers. What we look for This opportunity is a good fit for mathematicians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - Degree in Mathematics (Pure or Applied) or related fields; - Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; - 2+ years of professional experience: applied, research, or teaching experience is applicable; - Experience with numerical methods and symbolic computation; - Ability to design problems that mirror real mathematical research workflows; - Familiarity with computational complexity theory; - Strong written English (C1+). How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $76 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may:  - Design original computational mathematics problems that simulate real mathematical research workflows; - Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy); - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); - Develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis; - Base problems on real research challenges or practical applications from mathematical practice; - Verify solutions using Python with standard mathematical libraries; - Document problem statements clearly and provide verified correct answers. What we look for This opportunity is a good fit for mathematicians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - Degree in Mathematics (Pure or Applied) or related fields; - Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; - 2+ years of professional experience: applied, research, or teaching experience is applicable; - Experience with numerical methods and symbolic computation; - Ability to design problems that mirror real mathematical research workflows; - Familiarity with computational complexity theory; - Strong written English (C1+). How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $76 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

• Facilitating open-ended group tutoring sessions via Zoom for learners taking the Machine Learning specialisation (between May and August 2026, up to 4 hours a week) • Supporting learners with understanding core topics in Machine Learning (ML) and LLMs with Python technologies: from supervised and unsupervised learning with scikit-learn, to PyTorch for Deep Learning, as well as setting up tools such as Hugging Face Hub, GitHub and Llama 3 • Aligning advice with course content on DataCamp (full access provided) and Thrive’s overall learning objectives • Providing formative (interim mid-term) structured feedback on project work assignments and applied projects designed by the Applied AI Institute for Europe • Collaborating closely with the Learning Designer to align session delivery with curriculum goals • Providing lighter (1h/week) support between September and October, including evaluation of top learner projects and optional attendance at in-person graduation event (Berlin) • Contributing to continuous improvement of the Thrive program and ML specialization module through open feedback and constructive criticisms