Industrial Data Science Internship
Industrial Data Science Internship
We are looking for Master or recently graduated students to work on hands-on projects in the Digital Manufacturing / Industrial Data Science domain. If you are passionate about industrial process data analytics & optimization and you believe you have the right skill set and experiences, do not miss this unique opportunity!
Project description
The project will be focused on a process equipment represented by a combination of vessels, pipes and valves. Over 200 valves interconnected in a complex network of pipes. The chemical cleaning process consist of over 70 steps with different timers, flows and valves position targeting to clean all equipment and intersections.
Analysis, troubleshooting and optimization of this process with existing tools is extremely challenging, while cleaning efficiency is critical for line operation, stability of product quality, process downtime and wastewater generation.
As an Industrial Data Science Intern, you will have to develop a process model that enables the evaluation of current performance of cleaning-in-place process: time, flow at each section of the manifold: physical network of pipes and equipment connected and operated with valves.
Based on time series dataset with information of valves position (open or close), flowrates, time intervals, etc., the model should enable to quickly analyse the chemical cleaning efficiency of each individual pipe section (flow, temperature, time, etc.) and provide a performance report. The model should also enable further process optimization recommendations by evaluating different inputs and its predicted outcome.
What will make you a successful candidate
- MSc in Applied Data Science or Engineering (Industrial, Chemical, Biotechnology, etc.)
- Practical experience with programming languages (eg. Python, Matlab) is a must
- Network graph analysis, mathematical optimization and predictive modelling experience is a plus
We are Nestlé, the largest food and beverage company. We are 308,000 employees strong driven by the purpose of enhancing the quality of life and contributing to a healthier future. Our values are rooted in respect: respect for ourselves, respect for others, respect for diversity and respect for our future. With more than CHF 91.4 billion sales in 2018, we have an expansive presence with 413 factories in more than 85 countries. We believe our people are our most important asset, so we'll offer you a dynamic inclusive international working environment with many opportunities across different businesses, functions and geographies, working with diverse teams and cultures. Want to learn more? Visit us at www.nestle.com.
We are looking for Master or recently graduated students to work on hands-on projects in the Digital Manufacturing / Industrial Data Science domain. If you are passionate about industrial process data analytics & optimization and you believe you have the right skill set and experiences, do not miss this unique opportunity!
Project description
The project will be focused on a process equipment represented by a combination of vessels, pipes and valves. Over 200 valves interconnected in a complex network of pipes. The chemical cleaning process consist of over 70 steps with different timers, flows and valves position targeting to clean all equipment and intersections.
Analysis, troubleshooting and optimization of this process with existing tools is extremely challenging, while cleaning efficiency is critical for line operation, stability of product quality, process downtime and wastewater generation.
As an Industrial Data Science Intern, you will have to develop a process model that enables the evaluation of current performance of cleaning-in-place process: time, flow at each section of the manifold: physical network of pipes and equipment connected and operated with valves.
Based on time series dataset with information of valves position (open or close), flowrates, time intervals, etc., the model should enable to quickly analyse the chemical cleaning efficiency of each individual pipe section (flow, temperature, time, etc.) and provide a performance report. The model should also enable further process optimization recommendations by evaluating different inputs and its predicted outcome.
What will make you a successful candidate
- MSc in Applied Data Science or Engineering (Industrial, Chemical, Biotechnology, etc.)
- Practical experience with programming languages (eg. Python, Matlab) is a must
- Network graph analysis, mathematical optimization and predictive modelling experience is a plus
We are Nestlé, the largest food and beverage company. We are 308,000 employees strong driven by the purpose of enhancing the quality of life and contributing to a healthier future. Our values are rooted in respect: respect for ourselves, respect for others, respect for diversity and respect for our future. With more than CHF 91.4 billion sales in 2018, we have an expansive presence with 413 factories in more than 85 countries. We believe our people are our most important asset, so we'll offer you a dynamic inclusive international working environment with many opportunities across different businesses, functions and geographies, working with diverse teams and cultures. Want to learn more? Visit us at www.nestle.com.
Girona, Gerona, ES, 17007
Girona, Gerona, ES, 17007