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- Tasks: Help reproduce results from a cutting-edge deep learning paper in computer vision.
- Company: Join a forward-thinking team focused on innovative research and development.
- Benefits: Flexible contract, opportunity to work with advanced technologies, and enhance your skills.
- Why this job: Make a real impact in the AI field while working on exciting projects.
- Qualifications: Strong PyTorch experience and familiarity with human pose estimation required.
- Other info: Ideal for those looking to deepen their research skills in a dynamic environment.
The predicted salary is between 1500 - 2000 £ per month.
I need help reproducing the results of a published computer vision and human pose estimation paper. The work involves 3D human pose estimation from video using graph-based transformer architectures.
What you'll do:
- Set up and run the provided codebase (PyTorch-based).
- Reproduce training and evaluation on standard benchmark datasets.
- Match the reported performance metrics from the paper.
Required skills:
- Strong experience with PyTorch and deep learning.
- Familiarity with human pose estimation or skeleton-based action recognition.
- Experience with graph neural networks (GNN) and/or transformers.
- Comfortable working with research code and HPC/GPU environments.
- Ability to read and implement from academic papers.
Please include examples of similar work (paper reproduction, research implementation, or pose estimation projects) in your proposal.
Contract duration of 1 to 3 months.
Mandatory skills: Machine Learning, Python, Deep Learning, Neural Network, Computer Vision
Looking for a Researcher/Developer to Reproduce a Deep Learning Paper employer: FreelanceJobs
Contact Detail:
FreelanceJobs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Looking for a Researcher/Developer to Reproduce a Deep Learning Paper
✨Tip Number 1
Network like a pro! Reach out to professionals in the deep learning and computer vision fields on platforms like LinkedIn. Join relevant groups, participate in discussions, and don’t hesitate to ask for advice or insights about the role you're eyeing.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous work related to PyTorch, human pose estimation, or any relevant projects. This will give potential employers a clear idea of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on the latest research in deep learning and graph-based transformers. Be ready to discuss how you would approach reproducing results from academic papers, as this will demonstrate your expertise and problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Looking for a Researcher/Developer to Reproduce a Deep Learning Paper
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with PyTorch and deep learning in your application. We want to see how you've tackled similar projects, especially in human pose estimation or using graph-based architectures.
Be Specific About Your Experience: When you mention your past work, be specific! Include details about the datasets you used, the performance metrics you achieved, and any challenges you overcame. This helps us understand your problem-solving skills.
Follow the Instructions: Don’t forget to include examples of your previous work as requested. Whether it’s a paper reproduction or a project on pose estimation, we want to see what you’ve done. It shows us you can follow guidelines!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to keep track of your application and ensure you don’t miss out on this opportunity!
How to prepare for a job interview at FreelanceJobs
✨Know Your Stuff
Make sure you brush up on your PyTorch skills and understand the deep learning concepts related to human pose estimation. Familiarise yourself with the specific paper you'll be discussing, and be ready to explain how you would reproduce its results.
✨Showcase Your Experience
Prepare to share examples of your previous work that align with the job requirements. Whether it's a project on pose estimation or reproducing research papers, having concrete examples will demonstrate your capability and experience.
✨Ask Smart Questions
During the interview, don’t hesitate to ask insightful questions about the codebase or the benchmarks they use. This shows your genuine interest in the role and helps you gauge if the position is the right fit for you.
✨Be Ready for Technical Challenges
Expect some technical questions or even a coding challenge related to graph-based transformers or GNNs. Practising these types of problems beforehand can help you feel more confident and prepared.
