Data Science Intern: Roche Advanced Analytics Network - Biomedical Knowledge Graph machine learning

Praktikum nicht angegeben Bachelor

Roche is seeking an intern either pursuing, or recently graduated from a MSc/PhD degree with expertise in advanced analytics and machine learning to help us explore its potential applications in healthcare. You will join the Personalized Healthcare team and work on an innovative project applying advanced analytics and machine learning approaches to the company’s real world data, genomics, and clinical trial data assets spanning multiple disease areas.

Of particular interest will be the application of graph-based machine learning techniques.

We are looking for individuals who are:

  • Creative problem solvers, quick learners and comfortable experimenting with new approaches

  • Demonstrate high productivity and enjoys dealing with ambiguity and applying novel methodologies

  • Possess entrepreneurship, passion and curiosity for understanding and interrogating complex data.

Responsibilities:

  • Collaborate with the host team and other stakeholders to evaluate potential machine learning techniques and applications, especially in the field of biomedical knowledge graphs

  • Design, build and interpret machine learning algorithms to address selected research questions (including preparing the input data)

  • Proactively share learnings and knowledge to support the development of the wider Roche Advanced Analytics community

  • Help shape the direction of machine learning and artificial intelligence within Roche

Experience and Competencies Preferred:

  • Knowledge of a wide range of machine learning techniques and applications, with a focus on knowledge graph modeling and prediction

  • Experience applying machine learning algorithms and techniques, preferably to genomics and healthcare (EHR) data

  • Experience with mechanistic graph learning methods as well as representation learning and graph embeddings. Previous work with biological networks and knowledge graphs can be of advantage.

  • Experience with advanced missing data imputation methods and state-of-the-art mechanistic graph learning methods as well as representation learning and graph embeddings. Experience with biological networks and knowledge graphs can be of advantage.

  • Experience with technologies required to undertake analyses on large data sources or with computationally intensive steps (SQL, parallelization, Hadoop, Spark, HPC cluster computing, Docker)

  • Fluency in statistical programming languages (R, Python, etc.)

  • Strong communication and collaboration skills

  • Experience implementing reproducible research practices like version control (e.g. using Git) and literate programming

  • Demonstrated contributions to open source packages, libraries or functions

Qualifications Required:

  • MSc/PhD degree candidate or recent graduate in Data Science related field (e.g., Statistics, Mathematics, Epidemiology, Health Economics, Outcomes Research, Computer Science

Job Level:

Entry Level

Wer wir sind

At Roche, 100,000 people across 100 countries are pushing back the frontiers of healthcare. Working together, we’ve become one of the world’s leading research-focused healthcare groups. Our success is built on innovation, curiosity and diversity.

Roche is an equal opportunity employer.

Job-Fakten

  • StandortSwitzerland,Basel-City,Basel
  • Funktion Vocational & Development Programs
  • Subfunktion Internship
  • Arbeitszeit Full time
  • Funktionsebene Entry Level
  • Art der Anstellung Temporary (Fixed Term)
  • Firma/ Division Roche Pharmaceuticals
  • Posted since 2022/01/13
  • Job-ID 202201-100735

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Am 14.01.2022 veröffentlicht. Originalanzeige