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- Tasks: Refine AI models and create biochemistry problems from anywhere.
- Company: Leading AI research firm pushing the boundaries of science.
- Benefits: Earn $35-$70 per hour with flexible hours and competitive pay.
- Why this job: Engage with cutting-edge AI projects and make a real impact.
- Qualifications: PhD in Biochemistry or related field; no AI experience needed.
- Other info: Fully remote role with opportunities for growth in a dynamic field.
The predicted salary is between 27 - 54 £ per hour.
A leading AI research firm is looking for PhD-level Biochemists to refine AI models related to protein folding and metabolic analysis. In this fully remote role, you will create biochemistry problems and document AI reasoning errors, earning $35-$70 per hour.
Ideal candidates will have a PhD in Biochemistry or a related field, with no prior AI experience required. This position offers competitive pay, flexibility in hours, and the chance to engage with cutting-edge AI projects.
Remote Biochemist & AI Data Trainer | Flexible Hours in London employer: Alignerr
Contact Detail:
Alignerr Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote Biochemist & AI Data Trainer | Flexible Hours in London
✨Tip Number 1
Network like a pro! Reach out to fellow biochemists and AI enthusiasts on LinkedIn or relevant forums. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your biochemistry projects, especially any that relate to AI or data analysis. This will help you stand out and demonstrate your expertise in a practical way.
✨Tip Number 3
Prepare for interviews by brushing up on common questions related to biochemistry and AI. Practice explaining complex concepts in simple terms, as this will show your ability to communicate effectively with non-experts.
✨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, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Remote Biochemist & AI Data Trainer | Flexible Hours in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your PhD in Biochemistry and any relevant experience. We want to see how your background aligns with the role, so don’t be shy about showcasing your skills!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about the role and how your expertise can contribute to refining AI models. Keep it engaging and personal.
Showcase Your Problem-Solving Skills: Since you'll be creating biochemistry problems, give us examples of how you've tackled complex issues in the past. We love seeing your thought process and creativity!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves!
How to prepare for a job interview at Alignerr
✨Know Your Biochemistry Inside Out
Make sure you brush up on your biochemistry knowledge, especially around protein folding and metabolic analysis. Be ready to discuss your PhD research and how it relates to the role, as this will show your expertise and passion for the subject.
✨Familiarise Yourself with AI Basics
Even though prior AI experience isn't required, having a basic understanding of AI concepts can set you apart. Do some light reading on how AI models work, particularly in relation to biochemistry, so you can engage in meaningful discussions during the interview.
✨Prepare Thoughtful Questions
Interviews are a two-way street! Prepare insightful questions about the company's AI projects and how they integrate biochemistry. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.
✨Showcase Your Problem-Solving Skills
Be ready to discuss how you've tackled complex problems in your previous research. Highlight specific examples where you identified errors or improved processes, as this aligns perfectly with the role's focus on documenting AI reasoning errors.
