PhD Student | Genomics based Prediction Models

PhD Student | Genomics based Prediction Models

Published Deadline Location
20 Feb 12 Mar Amsterdam

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Help us find better predictive markers for lymphoma cancer and try to predict which therapy is best for which patient!

Job description

The project goal is to develop a novel methodological and computational framework that improves predictive biomarker signatures derived from cancer genomics data.

As PhD student in this project it’s your job: i) to train and compare tree-based machine learners (e.g. random forest and Bayesian additive regression trees) on high-dimensional data (i.e. data with more features than samples, e.g. genomics); ii) to adapt these methods to allow the inclusion of (big) ‘co-data’: auxiliary information on the genomic variables, such as genes. Examples for co-data are p-values from related external studies or data from cancer cell lines.

The result of your research will be ‘weighted learners’ that use importance weights for featuress in the high-dimensional data. The methodological challenge is to determine those weights in an automatic and objective way. Collaborators in oncology will support us with data and biomedical know-how. You will apply your approach to lymphoma cancer for the purpose of survival prediction, therapy response prediction, and personalized treatment allocation optimization. You will finalize the research with a PhD thesis.

Specifications

VU university medical center (VUmc)

Requirements

We are looking for a PhD student with the following experience and background:

  • You hold an MSc in Artificial Intelligence, Mathematics, Statistics, or a closely related discipline;
  • You have a strong background in quantitative modeling enabling the development of new computational methods;
  • You have strong programming skills, preferably in R, or are willing to learn R;
  • You are able to explain complex ideas to biologists/non-specialists;
  • Knowledge of supervised machine learning and/or survival analysis is an advantage;
  • You have good communication skills (written/oral) in English, you are self-disciplined and can work in a multi-disciplinary environment.

Conditions of employment

Fixed-term contract: 1 year with possible extension of 3 years.

Salary Scale OIO: 2422 tot 3103 euro gross when employed full-time (depending on qualifications and experience).

In addition we offer:

  • The base salary does not include allowances for irregular shifts, holiday pay (8%) and a year-end bonus (8.3%).
  • Pension is accrued at the ABP. VUmc contributes a large part of the premium (70%).
  • In addition to excellent accessibility by public transport, we reimburse 75% of your OV travel costs (commuting costs).

We offer an initial contract for one year that can be extended (after evaluation) for another 3 years.

For more information about our employment conditions, please visit our website.

Employer

The department of Epidemiology and Biostatistics at Amsterdam UMC, location VUmc, supports and initiates biomedical, epidemiological and biostatistical research. The department also coordinates the epidemiology and statistics courses for bachelor and master students. One of the main research topics is epidemiological, mathematical and cost-effectiveness research of the prevention, diagnosis and treatment of cancer.

You will join a dynamic international research team, and will collaborate with scientists with expertise in different disciplines. You will have the opportunity to follow high-quality courses offered by EpidM and the OOA oncology graduate school throughout your PhD.

Working at Amsterdam UMC means working in an inspiring and professional environment in which developing one`s talents and skills is encouraged. We offer you ample opportunity for development, deepening and broadening, additional training and a place to grow!

Specifications

  • PhD
  • Natural sciences; Engineering
  • max. 32 hours per week
  • €2422—€3103 per month
  • University graduate
  • D10.2020.00030BJ

Employer

VU university medical center (VUmc)

Learn more about this employer

Location

De Boelelaan 116, 1082 TR, Amsterdam

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