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- Tasks: Refine AI models and create biochemistry problems from anywhere.
- Company: Leading AI research firm at the forefront of innovation.
- 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 professional growth.
The predicted salary is between 26 - 52 £ 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 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
✨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 when chatting with potential employers.
✨Tip Number 3
Prepare for those interviews! Research common questions related to biochemistry and AI, and practice your responses. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications all in one place!
We think you need these skills to ace Remote Biochemist & AI Data Trainer | Flexible Hours
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! Use it to explain why you’re excited about working with AI and how your expertise in biochemistry can contribute to our projects. Keep it engaging and personal.
Showcase Your Problem-Solving Skills: Since you'll be creating biochemistry problems, it’s important to demonstrate your analytical thinking. Include examples of past challenges you've tackled and how you approached them. We love a good problem-solver!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any updates from us!
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 conversations 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 past 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.
