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- Tasks: Analyse and interpret high-plex spatial biology data remotely.
- Company: Join a leading pharmaceutical company making waves in the industry.
- Benefits: Enjoy a long-term contract, remote work, and flexibility outside IR35.
- Why this job: Be at the forefront of innovative research with a dynamic team.
- Qualifications: Experience in scRNA-seq, spatial transcriptomics, R or Python required.
- Other info: Perfect for those passionate about genomics and machine learning.
The predicted salary is between 43200 - 72000 £ per year.
This is a fantastic opportunity to work as a Bioinformatician on a long term, remote contract, outside IR35, for a major pharmaceutical company. This Bioinformatician will be analyzing and interpreting high-plex spatial biology data. The skills required for this Bioinformatician position are: scRNA-seq, spatial transcriptomics multi-IF, genomics (e.g., whole genome sequencing) clinical imaging (e.g., digital histopathology) R or Python Statistical analysis, machine learning techniques, and data visualization methods. If you do have the relevant experience for this Bioinformatician position, please do apply
Bioinformatician - Spatial Transcriptomics - Remote - Outside IR35 employer: The Bridge IT Recruitment
Contact Detail:
The Bridge IT Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Bioinformatician - Spatial Transcriptomics - Remote - Outside IR35
✨Tip Number 1
Make sure to showcase your experience with scRNA-seq and spatial transcriptomics in your conversations. Highlight specific projects where you've successfully applied these techniques, as this will demonstrate your hands-on expertise.
✨Tip Number 2
Familiarise yourself with the latest advancements in machine learning techniques relevant to bioinformatics. Being able to discuss recent trends or tools can set you apart during interviews and show your commitment to staying updated in the field.
✨Tip Number 3
Prepare to discuss your experience with data visualisation methods. Bring examples of how you've effectively communicated complex data findings in previous roles, as this is crucial for a Bioinformatician working with high-plex spatial biology data.
✨Tip Number 4
Network with professionals in the bioinformatics community, especially those focused on spatial transcriptomics. Engaging in discussions or attending relevant webinars can provide insights and connections that may help you land the job.
We think you need these skills to ace Bioinformatician - Spatial Transcriptomics - Remote - Outside IR35
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with scRNA-seq, spatial transcriptomics, and any relevant programming skills in R or Python. Use specific examples to demonstrate your expertise in statistical analysis and machine learning techniques.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background in bioinformatics and your experience with high-plex spatial biology data make you a strong candidate for this position.
Showcase Relevant Projects: If you have worked on projects involving clinical imaging or data visualisation methods, be sure to mention these in your application. Providing concrete examples of your work can set you apart from other candidates.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors or typos. A polished application reflects your attention to detail, which is crucial in the field of bioinformatics.
How to prepare for a job interview at The Bridge IT Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your experience with scRNA-seq, spatial transcriptomics, and other relevant techniques. Highlight specific projects where you've applied these skills, as this will demonstrate your expertise and suitability for the role.
✨Prepare for Data Analysis Questions
Expect questions that assess your proficiency in R or Python, especially in relation to statistical analysis and machine learning. Brush up on common algorithms and be ready to explain how you've used them in past projects.
✨Familiarise Yourself with Clinical Imaging
Since the role involves clinical imaging, review concepts related to digital histopathology. Being able to discuss how you interpret imaging data can set you apart from other candidates.
✨Demonstrate Your Problem-Solving Skills
Prepare to discuss challenges you've faced in previous roles and how you overcame them. This could involve troubleshooting data issues or optimising analysis workflows, showcasing your analytical thinking and adaptability.
