Graduate Internship: AI, ML & Physics-Informed Modeling

Boskalis

Papendrecht

Hybrid

EUR 5,600 - 7,800

Full time

14 days+
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Benefits offered by this job

Internship allowance
Young Boskalis
Databricks access
Office in Papendrecht (3 days a week)

Job summary

Boskalis is looking for a master's student to start a graduation project in Papendrecht. You will explore physics-informed machine learning, time-series modelling, and adaptive control to improve our data-driven dredging operation settings based on historical data.

You will collaborate with data scientists and engineers, perform literature research, and formulate a hybrid modeling approach. Supervision from AI experts and access to Databricks are provided, plus an internship allowance and Young

Qualifications

  • Currently pursuing a university master's degree in a relevant field.
  • Affinity with Python and version control.
  • Able to develop, train, and evaluate ML models.
  • Theoretical understanding of physics-informed ML, time-series modelling, or adaptive control; practical knowledge is a plus.
  • Proficient in writing reports and presenting results.
  • Preference for working at our office in Papendrecht at least 3 days a week.

Responsibilities

  • Work with data scientists and engineers to understand the challenge.
  • Conduct literature research on physics-informed ML, time-series modelling, and adaptive control.
  • Formulate a problem that combines physical knowledge with data-driven models.
  • Develop methods to improve the model's recommendations and demonstrate generalization across vessels and conditions.
  • Report final findings with reproducible results.

Job description

Boskalis is looking for a master's student to start a graduation project in Papendrecht. You will explore physics-informed machine learning, time-series modelling, and adaptive control to improve our data-driven dredging operation settings based on historical data.

You will collaborate with data scientists and engineers, perform literature research, and formulate a hybrid modeling approach. Supervision from AI experts and access to Databricks are provided, plus an internship allowance and Young

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