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- Tasks: Design and develop advanced Graph Neural Network models for oil & gas applications.
- Company: Leading technology firm at the forefront of innovation.
- Benefits: Competitive salary, travel opportunities, and professional growth.
- Why this job: Make a real impact in the oil & gas industry with cutting-edge technology.
- Qualifications: MS/PhD in relevant fields and expertise in Graph Neural Networks.
- Other info: Initial business trip to Kuwait for hands-on experience.
The predicted salary is between 36000 - 60000 £ per year.
A leading technology firm is looking for a skilled Machine Learning Engineer to develop advanced Graph Neural Network models for oil & gas applications. The role involves designing neural networks, building predictive models, and collaborating with engineers.
Candidates should hold an MS/PhD in relevant fields and have deep expertise in Graph Neural Networks, alongside strong Python skills. This position requires a business trip to Kuwait for the initial months and aims at significant contributions to advanced engineering projects.
GNN Engineer for Physics Surrogates in Oil & Gas employer: Luxoft
Contact Detail:
Luxoft Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GNN Engineer for Physics Surrogates in Oil & Gas
✨Tip Number 1
Network like a pro! Reach out to professionals in the oil & gas sector, especially those working with Graph Neural Networks. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to machine learning and Graph Neural Networks. This can be a game-changer during interviews, as it gives potential employers a tangible sense of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and understanding of neural networks. Practice coding challenges and be ready to discuss your past projects in detail. We all know that confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search. Let’s get you that GNN Engineer role!
We think you need these skills to ace GNN Engineer for Physics Surrogates in Oil & Gas
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your expertise in Graph Neural Networks and Python in your application. We want to see how your skills align with the role, so don’t hold back on showcasing your projects or experiences!
Tailor Your Application: Take a moment to customise your CV and cover letter for this specific role. We love seeing candidates who understand the oil & gas industry and can relate their experience to our needs. It shows us you’re genuinely interested!
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and enthusiasm for the position.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Luxoft
✨Know Your Graph Neural Networks
Make sure you brush up on your knowledge of Graph Neural Networks. Be prepared to discuss specific models you've worked on, the challenges you faced, and how you overcame them. This will show your depth of expertise and passion for the field.
✨Showcase Your Python Skills
Since strong Python skills are a must, be ready to demonstrate your coding abilities. You might be asked to solve a problem on the spot or explain your thought process behind a piece of code. Practising common algorithms and data structures in Python can give you an edge.
✨Understand the Oil & Gas Industry
Familiarise yourself with the specific applications of machine learning in the oil and gas sector. Knowing how GNNs can optimise operations or predict outcomes in this industry will help you connect your technical skills to real-world problems, making you a more attractive candidate.
✨Prepare for Collaboration Questions
As the role involves collaborating with engineers, expect questions about teamwork and communication. Think of examples where you've successfully worked in a team, especially in cross-disciplinary settings. Highlight your ability to convey complex ideas clearly and effectively.
