Mathematics Expert
@ Taskify

Hybrid
$120,000
Hybrid
Part Time
Posted 11 hours ago

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XXXXXXXX XXXXXXXXX XXXXXXX***** @taskify.com
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Job Details

About the Role

Are you a recent Mathematics PhD or advanced PhD candidate from a top 30 program? Join a cutting-edge AI research project to strengthen machine reasoning and theorem-solving capabilities. Your expertise will directly shape the next generation of AI mathematical intelligence.

Key Responsibilities

  • Solve and assess complex mathematics problems across various fields.
  • Review AI-generated proofs and solutions for accuracy, rigor, and clarity.
  • Provide structured feedback to improve AI reasoning and theorem validation.

Qualifications / Skills Required

  • PhD in Mathematics (within the past 4 years) OR ≥3 years into a PhD program.
  • Enrolled in or graduated from a top 30 Mathematics program.
  • Strong problem-solving, theorem-referencing, and analytical communication skills.

Preferred Qualifications

  • Active in academic research or publications.
  • Experience mentoring or teaching advanced mathematics.

Why Join

Flexible, project-based contract (5–6 weeks, with potential for extension). Apply your graduate-level expertise to cutting-edge AI systems and collaborate with a leading AI research group shaping future reasoning models.

Key skills/competency

Mathematics, AI, problem-solving, theorem, research, analytical, proofs, feedback, mentoring, communication

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How to Get Hired at Taskify

🎯 Tips for Getting Hired

  • Customize your resume: Emphasize AI and mathematics research skills.
  • Highlight academic achievements: Include top program credentials.
  • Prepare examples: Share problem-solving and proof reviewing experience.
  • Research Taskify: Understand company mission and projects.

📝 Interview Preparation Advice

Technical Preparation

Review advanced math problem sets.
Study AI proof evaluation methods.
Familiarize with theorem-solving techniques.
Brush up on analytical reasoning approaches.

Behavioral Questions

Describe a challenging research problem solved.
Explain collaboration with academic peers.
Detail feedback provision experiences.
Discuss adaptability in evolving projects.

Frequently Asked Questions