Winter- Spring 2025 Co-Op, Computational Antigen Design - Vaccine at Sanofi in Waltham, Massachusetts

Job Description:

About the Job



We are an innovative global healthcare company that helps the world stay ahead of infectious diseases by delivering more than 500 million vaccine doses a year. Across different countries, our talented teams are exploring new technologies to protect people and promote healthy communities. We chase the miracles of science every single day, pursuing progress to make a real impact on millions of patients around the world.



**At this time, Sanofi will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, or another type of work authorization). **




Essential Duties and Responsibilities

• The candidate is expected to learn modern bioinformatics tools and machine learning techniques to build, test, and deploy population genetics and functional models of viral evolution
  
  


• The candidate is expected to contribute to the development of data analysis and decision support tools focusing on genetic and epidemiological surveillance and predictive modeling
  
  


• The candidate is expected to prepare, analyze, and interpret data regarding the genetic composition, epidemiology, fitness, and structure of viral proteins
  
  


• Role will require design, coding, implementation, training, validation, and maintenance of machine learning models and bioinformatics pipelines
  
  


• This is a hands-on computational, office-based role in a highly collaborative, multidisciplinary vaccine design environment
  
  


• Participate in scientific discussions on epidemiology, computational biology, bioinformatics, and machine learning
  
  


• Maintain detailed records, contribute to the code base repository, and proactively communicate progress and challenges
  
  

About you




Basic Qualifications:

• Currently pursuing a PhD in Computational Biology, Bioinformatics, Population Genetics, Epidemiology, or related discipline
  
  


• Must have permanent US work authorization
  
  


• Must be able to relocate to our Waltham office location and complete the full duration on the Co-op
  
  


• Background in biological data analysis is required
  
  

Preferred Qualifications:

• Practical experience with machine learning modeling is highly desirable
  
  


• Experience with large bioinformatics databases, such as Genbank, SRA, EMBL, and GISAID is highly desirable
  
  


• Exposure to computational structural biology and protein modeling desirable
  
  


• Proficient in Python, SQL, sequence alignment and phylogenetic analysis tools, and machine learning libraries, in a high throughput or cloud environments in Linux
  
  


• Experience with scientific visualization and interactive dashboard design (R-Shiny, Plotly, Bokeh, Flask) a plus
  
  


• Strong interpersonal, communication, and presentation skills
  
  

Why Choose Us?

• Bring the miracles of science to life alongside a supportive, future-focused team.
  
  


• Discover endless opportunities to grow your talent and drive your career, whether it's through a promotion or lateral move, at home or internationally.
  
  


• Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.
  
  


• Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs and at least 14 weeks' gender-neutral parental leave.
  
  

**At this time, Sanofi will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, or another type of work authorization). **



Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.


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