Job Description

Description

About Immunai:

Immunai is an AI-driven platform company focused on improving drug discovery and development by decoding the human immune system.

We combine large-scale single cell immune data, advanced machine learning, and strong engineering to help pharmaceutical and research partners make better, more informed decisions throughout the drug development process.

Our long-term goal is to reduce drug development failure rates and help more effective medicines reach patients. We're building this platform thoughtfully and collaboratively, bringing together expertise across biology, AI, engineering, and business.

Immunai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

About the role:

As a Senior Computational Biologist at Immunai, you will be working in a fast-paced and research-driven external collaborations team to lead projects with our pharma, biotech, and academic partners. Through this position, you will have the opportunity to work with biologists, immunologists, computational biologists, machine learning specialists, and the business development team to design, execute, and disseminate data analyses leveraging single cell multi-omics for immuno-oncology and autoimmune disease research applications.

Location: New York City, NY (Hybrid model)

What will you do?

• Drive novel research by leading computational biology efforts for industry and academic partnership projects in immuno-oncology and autoimmune diseases
• Liaise with external and internal stakeholders to define research objectives and analysis plans
• Execute rigorous and reproducible data analysis using state of the art methods
• Maintain close collaboration with a highly multidisciplinary internal team throughout the life cycle of each project to ensure successful delivery
• Clearly communicate findings to external stakeholders in the form of presentations and data reports
• Devise and implement new approaches to push the boundaries of Immunai's capabilities, including through the effective utilization of LLM-based tools
• Champion Immunai core values

Requirements

Required qualifications:

• Experience in multi-omic data analysis including bulk and single-cell transcriptomics (8-10 yrs relevant experience; MSc w/ 6+ yrs experience or PhD w/ 2+ years postdoctoral experience)
• Expertise in current bioinformatics and computational biology tools, methods, and applications; Strong ability to develop and test data analysis code (R or Python's pandas)
• Background and experience with machine learning methodologies and continued interest in learning and applying ML approaches
• Expertise in distilling multi-faceted analyses into concrete conclusions with effective data visualizations and presentations
• Experience leading large scale initiatives and projects demonstrated through first author peer-reviewed publications in relevant subject areas and/or project lead roles in industry positions
• Keen interest in biology and immunology with demonstrated research experience in immuno-oncology and/or autoimmune diseases; experience in CAR-T biology is a plus.
• Excellent verbal and written communication skills to represent Immunai to external collaborators as well as operate effectively on a diverse and collaborative internal team

Desired personal traits:

• You want to make an impact on humankind
• You prioritize "We" over "I"
• You enjoy getting things done and striving for excellence
• You collaborate effectively with people of diverse backgrounds and cultures
• You have a growth mindset
• You are candid, authentic, and transparent

Compensation: This position offers a base salary typically between $150,000 and $160,000. There is an opportunity to consider higher compensation above this range based on business need, candidate experience, and or skills.

*Please note that when you apply for a position at Immunai, your application will be processed via our recruitment platform Comeet. You can read more about how we process personal data here:

Job Tags

Full time

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