Research Scientist in Data Science (m/f/d)

Key Skills

Aartificial intelligence, Data science techniques, Effective communication skills, Machine learning techniques, Python Programming, Teamwork, User support and Troubleshooting

Job Description

• Develop and implement bioinformatic pipelines to interpret omic data sets in order to drive mechanistic-based screening and support development of safe plant protection products:
• Optimize and develop omics data (transcriptomic, cell painting and metabolomic) analysis workflows
• Review appropriate literature pertaining to current or proposed projects
• Leveraging unsupervised learning to discover biologically-relevant patterns associated with Toxicity endpoints
• Utilize AI/machine learning techniques to analyze and interpret complex biological data
• Independently plan, analyze, interpret your data analysis, set-up critical path and path-forward
• Communicate and report study findings, results, analyses, and future direction to project partners (to direct manager & collaborators)
• Actively collaborate within the toxicology and omics communities within Bayer
• Participate in project meetings and active scientific exchange with internal and external scientific communities

QUALIFICATIONS AND COMPETENCIES :

Education:

• PhD in bioinformatic, cellular biology, biology, toxicology, or related disciplines
• 2 years of experience in academic, pharmaceutical, or biotechnology settings.

Skills:

• 2 years of experience in academic, pharmaceutical, or biotechnology settings
• Strong expertise in scripting. Python languages applied to omics data is required
• Utilize AI/machine learning techniques to analyze and interpret complex biological data
• Experience in high content screening technology (384 wells), and high throughput quantitative data analysis would be a plus
• Demonstrated experience with global multi-disciplinary teams
• Strong personal organization skills are required
• Excellent verbal and written communication skills
• Proficient in English, basic knowledge of French is an advantage

Additional considerations:

• Knowledge of emerging technologies and motivation to implement innovative scientific strategy and lab operations
• Experience in machine learning methods is required
• Ability to troubleshoot problems and provide possible solutions
• Capable of conveying technical information in a clear and thorough manner
• Excellent interpersonal and teamwork skills

OTHER INFORMATIONS :

Location: Sophia-Antipolis near Nice (06), France

Division: Crop Science