At a Glance
- Tasks: Develop cutting-edge machine learning functions for real-time detection of cassava viral infections.
- Company: Join a global team from top universities and research institutes.
- Benefits: Enjoy a pension scheme, health services, generous leave, and discounts.
- Other info: Opportunities for professional development and travel in a dynamic environment.
- Why this job: Make a real-world impact on agriculture with innovative technology.
- Qualifications: Experience in machine learning, programming, and working in diverse teams.
The predicted salary is between 45000 - 60000 € per year.
Overview: The overall role is to develop advanced multispectral image processing and machine learning functions on a real-time embedded system for detecting cassava viral infection from scanned leaves in the field. This role is part of a multidisciplinary, international project between Rutgers University (USA), North Carolina State University (USA), International Institute of Tropical Agriculture (IITA) (Tanzania), Rothamsted Research (UK), and the University of Manchester (UK). The role contributes to the development of machine learning algorithms on in-house built low-cost multispectral imaging systems for detecting cassava brown streak virus in the field. The project aims to expand the technology to in-situ detection, characterization and monitoring of cassava growth and quality control, funded through the NSF and BBSRC Joint Programme (EEID). There are professional development and travel budgets and opportunities.
Responsibilities:
- Develop advanced multispectral image processing and machine learning functions on real-time embedded systems.
- Collaborate with international project partners to integrate algorithms with hardware platforms.
- Validate and optimize detection of cassava brown streak virus in field conditions.
- Contribute to field deployment, data collection, and ongoing system improvements.
Qualifications:
- Experience in multispectral imaging, computer vision, and machine learning for embedded or real-time systems.
- Strong programming skills (e.g., Python, C/C++, MATLAB) and experience with ML frameworks.
- Ability to work in a multidisciplinary, international team and in field conditions.
Benefits:
- Pension scheme
- Employee health and wellbeing services including an Employee Assistance Programme
- Starting annual leave entitlement plus bank holidays
- Additional paid closure over the Christmas period
- Local and national discounts at retailers
Equal Opportunity: As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit. Hybrid working arrangements may be considered.
Machine Learning Specialist employer: The University of Manchester
As a Machine Learning Specialist, you will join a dynamic and innovative team dedicated to advancing agricultural technology through cutting-edge research and development. Our collaborative work culture fosters professional growth and offers unique opportunities for international travel and engagement with leading experts in the field. With a strong commitment to employee wellbeing and a supportive environment, we ensure that our team members thrive both personally and professionally while making a meaningful impact on global food security.
Contact Detail:
The University of Manchester Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Specialist
✨Tip Number 1
Network like a pro! Reach out to your connections in the machine learning and imaging fields. Attend relevant meetups or webinars, and don’t be shy about asking for introductions. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to multispectral imaging and machine learning. We recommend including any relevant code snippets or results from your work. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you might need to collaborate with non-technical team members. We suggest doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive and engaged. So, go ahead and submit your application – we can’t wait to see what you’ve got!
We think you need these skills to ace Machine Learning Specialist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in multispectral imaging and machine learning. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about this project and how your background makes you a perfect fit. We love seeing enthusiasm and a personal touch!
Showcase Your Technical Skills:Since we’re looking for someone with strong programming skills, make sure to mention your proficiency in Python, C/C++, or MATLAB. If you’ve worked with ML frameworks, give us the details – we want to know what you can bring to the table!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the easiest way for us to keep track of your application and ensures you don’t miss any important updates. Plus, we love seeing applications come in through our own channels!
How to prepare for a job interview at The University of Manchester
✨Know Your Tech
Make sure you brush up on your knowledge of multispectral imaging and machine learning algorithms. Be ready to discuss specific projects you've worked on, especially those involving real-time embedded systems. This will show that you not only understand the theory but also have practical experience.
✨Collaborate Like a Pro
Since this role involves working with international partners, be prepared to talk about your experience in multidisciplinary teams. Share examples of how you've successfully collaborated with others, especially in challenging environments or field conditions.
✨Showcase Your Coding Skills
You’ll need strong programming skills, so be ready to demonstrate your proficiency in Python, C/C++, or MATLAB. Consider preparing a small coding challenge or discussing a piece of code you've written that relates to machine learning or image processing.
✨Ask Insightful Questions
Prepare thoughtful questions about the project and its goals. Inquire about the challenges they face in detecting cassava viral infections and how your role could contribute to overcoming them. This shows your genuine interest and helps you understand if the role is the right fit for you.
