
Master Thesis Internship - AI Applications in Pharma Technical Operations
Are you a highly motivated and ambitious student looking to gain practical experience in the field of artificial intelligence (AI) and its applications in pharmaceutical technical operations? Look no further than Roche's Master Thesis Internship program! As a global leader in the healthcare industry, Roche is dedicated to developing innovative solutions to improve patient outcomes. In this role, you will have the opportunity to work alongside our team of experts to research and develop cutting-edge AI applications for our technical operations in the pharmaceutical sector. We are seeking a driven and curious individual with a strong academic background in computer science, engineering, or a related field. If you are passionate about leveraging AI to revolutionize the healthcare industry, we want to hear from you!
- Conduct research on the latest developments in artificial intelligence and its applications in pharmaceutical technical operations.
- Collaborate with the team to identify potential areas where AI can be implemented to improve processes and operations.
- Develop and implement AI algorithms and models to support the technical operations in the pharmaceutical sector.
- Analyze data and provide insights to improve the efficiency and effectiveness of processes using AI.
- Work closely with cross-functional teams to integrate AI solutions into existing systems and processes.
- Perform tests and experiments to evaluate the performance of AI applications and make necessary improvements.
- Document findings and present them to stakeholders, including senior management.
- Stay updated on advancements in AI technology and provide recommendations for future projects and initiatives.
- Take ownership of assigned tasks and deliver high-quality results within given timelines.
- Adhere to company policies and procedures, as well as ethical and legal standards related to AI research and development.
Strong Academic Background: Candidates For This Internship Should Have A Demonstrated Record Of Academic Excellence, Particularly In The Fields Of Artificial Intelligence And Pharmaceutical Sciences.
Relevant Coursework: A Background In Relevant Coursework Such As Machine Learning, Data Analytics, And Drug Development Will Be Highly Valued For This Position.
Previous Research Experience: Roche Is Looking For Candidates With Previous Research Experience, Preferably In The Fields Of Ai And Pharmaceutical Sciences. This Could Include Participation In Research Projects, Publications, Or Presentations.
Programming Skills: Proficiency In Programming Languages Such As Python, R, And Sql Is Essential For This Role. Candidates Should Be Able To Demonstrate Their Ability To Apply These Skills In Practical Settings.
Strong Interest In Pharmaceutical Industry: The Ideal Candidate Will Have A Strong Interest In The Pharmaceutical Industry And A Desire To Use Ai To Improve Processes And Operations In The Industry. Knowledge Of Current Trends And Challenges In The Industry Will Be A Plus.
Programming
Data Analysis
statistical analysis
Big Data
Machine Learning
Deep Learning
Automation
Natural language processing
Algorithm development
Predictive modeling
Neural Networks
image recognition
Communication
Conflict Resolution
Emotional Intelligence
Leadership
Time management
creativity
Critical thinking
Teamwork
Adaptability
Problem-Solving
According to JobzMall, the average salary range for a Master Thesis Internship - AI Applications in Pharma Technical Operations in Basel, Switzerland is between CHF 3,000 to CHF 4,500 per month. This may vary depending on the specific company, industry, and individual qualifications and experience.
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Roche Holding AG operates as a research healthcare company. It operates through the diagnostics and pharmaceuticals segments. The pharmaceutical segment refers to development of medicines in the field of oncology, immunology, ophthalmology, infectious diseases and neuroscience. The diagnostic segment refers to diagnosis of diseases through an in vitro diagnostics process.

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