You are here: Home Jobs

Jobs

The Interdisciplinary Research Unit Mathematics and Life Sciences has currently the following job openings:

PhD in Multi-Cellular Systems Biology

Most biological tissues consist of many different cell types and are highly organized. The corresponding spatio-temporal patterns are relevant in many biological and biomedical processes including tissue homeostasis, viral infection or tumor development, and can be studied with imaging techniques, such as light and fluorescence microscopy. Biomedical imaging data provides quantitative information about biological systems, however, mechanisms causing spatial patterning and causalities often remain elusive. To close this gap, multi-scale computational modelling can be employed.

The goal of this project is to develop a computational pipeline for the analysis of tissue dynamics. The research project with focus on model development and parameterization. The project is part of the collaborative research project FitMultiCell in which a novel pipeline for the model-based analysis of imaging data is to be established. The methods are based on some of our recent work on multi-scale modelling ( Jagielle et al., Cell Syst., 2017; Klinger et al., Bioinf., 2018). Applications will focus on the modelling of virus transmission modes in biological tissues. Knowledge about transmission modes will facilitate the design of more effective anti-viral treatments.

Job description:

  • Development of multi-cellular models (e.g., virus transmission)
  • Development of scalable parameter estimation methods for multi-cellular models
  • Implementation of methods for high-performance computing (HPC) infrastructures
  • Application of methods and interpretation of the results
  • Collaboration with national and international partners

Your profile:

  • Master degree in computer science, engineering, mathematics, physics or equivalent
  • Background in computational modeling, statistical inference or machine learning
  • Programming experience (preferably Python and/or C++)
  • Background in HPC
  • Proficiency in written and spoken English
  • Passion for science and scientific work

Our offer:

  • Working in an innovative, well-equipped and scientifically stimulating environment
  • Further training opportunities
  • Initial short-term employment contract for 3 years with a standard public service salary (TV-L EG 13, 75%)

The deadline for the application round is March 30, 2021.

Application documents (cover letter, CV, certificates, two reference letters) should be submitted as soon as possible as a single PDF file via email.

Contact: Prof. Dr. Jan Hasenauer, [Email protection active, please enable JavaScript.]

PostDoc in Computational Epidemiology (focusing on SARS-CoV-2)

The EU project ORCHESTRA provides an innovative approach to learn from the pandemic SARS-CoV-2 crisis and derive recommendations to be better prepared for future pandemics. The ORCHESTRA project aims to deliver scientific evidence for the prevention and treatment of infections and assess epidemiological, clinical, microbiological, and genotypic aspects of population, environment and socio-economic features. The project builds up on existing and new large scale population cohorts in Europe (France, Germany, Spain, Italy, Belgium, Romania, Netherlands, Portugal, Luxemburg, and Slovakia) and non-European countries (India, Peru, Ecuador, Colombia, Venezuela, Argentina, Brazil, Congo, and Gabon) including SARS-CoV-2 infected and non-infected individuals of all ages and conditions. The main outcome of ORCHESTRA is the creation of a new pan-European cohort applying homogenous protocols for data collection, data sharing, sampling, and follow up, which can rapidly advance the knowledge on the control and management of the COVID-19.

As leaders of the data analysis work package, we will exploit and develop novel federated learning approaches for the training of statistical and machine learning models, as well as (fine-grained) dynamical models. This will address the general problem of data exchange in data science, which is – in particular in health care – often limiting.

Job description:

  • (Federated) statistical analysis and machine learning for the analysis of comprehensive patient datasets

  • Dynamic mathematical modeling of the dynamics of the SARS-CoV-2 pandemic

  • Interpretation of analysis results

  • Collaboration with biologists and medical researchers

  • Publication of scientific results at conferences and in journals

  • Co-supervision of students

Your profile:

  • PhD degree in (bio-)informatics, computational biology, computer science, mathematics or equivalent

  • Strong experience in at least three of the following topics: Bioinformatics, statistics, mathematical modeling (ODEs or similar), machine learning, and data management/integration

  • Programming skills (e.g., R or Python)

  • Proficiency in written and spoken English

  • Passion for science and scientific work

Our offer:

  • Working in an innovative, well-equipped and scientifically stimulating environment

  • Further training opportunities

  • Initial fixed-term employment contract for 3 years with a standard public service salary (PostDoc: 100% TV EntgO Bund EG 13)


The deadline for the application round is March 30, 2021.

Application documents (cover letter, CV, certificates, two reference letters) should be submitted as soon as possible as a single PDF file via email.

Contact: Prof. Dr. Jan Hasenauer, [Email protection active, please enable JavaScript.]

PhD in Computational Epidemiology (focusing on SARS-CoV-2)

The EU project ORCHESTRA provides an innovative approach to learn from the pandemic SARS-CoV-2 crisis and derive recommendations to be better prepared for future pandemics. The ORCHESTRA project aims to deliver scientific evidence for the prevention and treatment of infections and assess epidemiological, clinical, microbiological, and genotypic aspects of population, environment and socio-economic features. The project builds up on existing and new large scale population cohorts in Europe (France, Germany, Spain, Italy, Belgium, Romania, Netherlands, Portugal, Luxemburg, and Slovakia) and non-European countries (India, Peru, Ecuador, Colombia, Venezuela, Argentina, Brazil, Congo, and Gabon) including SARS-CoV-2 infected and non-infected individuals of all ages and conditions. The main outcome of ORCHESTRA is the creation of a new pan-European cohort applying homogenous protocols for data collection, data sharing, sampling, and follow up, which can rapidly advance the knowledge on the control and management of the COVID-19.

As leaders of the data analysis work package, we will exploit and develop novel federated learning approaches for the training of statistical and machine learning models, as well as (fine-grained) dynamical models. This will address the general problem of data exchange in data science, which is – in particular in health care – often limiting.

Job description:

  • (Federated) statistical analysis and machine learning for the analysis of comprehensive patient datasets

  • Dynamic mathematical modeling of the dynamics of the SARS-CoV-2 pandemic

  • Programming (Python or R)

  • Interpretation of analysis results

  • Collaboration with biologists and medical researchers

  • Publication of scientific results at conferences and in journals

Your profile:

  • Master degree in (bio-)informatics, computational biology, computer science, mathematics or equivalent

  • Strong experience in at least two of the following topics: Bioinformatics, statistics, mathematical modeling (ODEs or similar), machine learning, and data management/integration

  • Programming skills (e.g., R or Python)

  • Proficiency in written and spoken English

  • Passion for science and scientific work

Our offer:

  • Working in an innovative, well-equipped and scientifically stimulating environment

  • Further training opportunities

  • Initial fixed-term employment contract for 3 years with a standard public service salary (PhD: 75% TV EntgO Bund EG 13)

The deadline for the application round is March 30, 2021.

Application documents (cover letter, CV, certificates, two reference letters) should be submitted as soon as possible as a single PDF file via email.

Contact: Prof. Dr. Jan Hasenauer, [Email protection active, please enable JavaScript.]

PhD at the interface of Computational Epidemiology and Finances

A public health crisis, such as a pandemic, requires decisive policy action. Governments can pursue a variety of non-pharmaceutical interventions of varying intrusiveness, ranging from voluntary social distancing of individuals to a mandatory shutdown of the country. These interventions do influence the spread of diseases and can avoid an overload of the health care system. However, they also impose an economic toll. Individuals respond to the new environment that reduces their ability to engage in work and consumption. Policy-makers need to navigate the trade-off between health benefits and the economic cost of any such policy. They require reliable information regarding the impact of alternative policy proposals that take into account the complex interactions between public health, the economy, and individual decisions.

In this project, we will combine epidemiological and economic models to provide policy-makers with such an integrated assessment of their policy choices. We will address the following questions:

  • What is the impact of alternative policy proposals on public health? How will individuals adjust their behavior, and are supporting measures needed to ensure adherence to the policy in light of resulting economic hardship?

  • What are the characteristics of policies that achieve a substantial health benefit while minimizing economic costs?

  • How do policy responses need to vary across countries to account for institutional differences such as existing social safety nets?

Using the insights and data generated by the current COVID-19 pandemic, we seek to inform decision making processes in current and future health challenges.

Job description:

  • Integrated mathematical modeling of epidemiological and micro-economic processes

  • Model-based analysis of complex data using sensitivity and uncertainty analysis

  • Programming (Python, R or Julia)

  • Interpretation of analysis results

  • Collaboration with biologists, medical researchers and economists

  • Publication of scientific results at conferences and in journals

Your profile:

  • Master degree in mathematics, computer science, physics, or related fields

  • Strong experience in at least two of the following topics: Mathematical modeling (e.g. ODEs or Markov processes), statistics, numerical optimization, machine learning, and high-performance computing

  • Programming skills (e.g., Python or Julia)

  • Proficiency in written and spoken English

  • Passion for science and scientific work

Our offer:

  • Working in an innovative, well-equipped and scientifically stimulating environment

  • Further training opportunities

  • Initial fixed-term employment contract for 3 years with a standard public service salary ( PhD : 75% TV EntgO Bund EG 13)

The deadline for the application round is March 30, 2021.

Application documents (cover letter, CV, certificates, two reference letters) should be submitted as soon as possible as a single PDF file via email.

Contact: Prof. Dr. Jan Hasenauer, [Email protection active, please enable JavaScript.]

PostDoc in Computational Biology (focusing on metainflammation)

The environment to which humans are exposed to in the developed, Western world has drastically changed, particularly in the last few decades. These changes, along with societal and economic developments, have led to dramatic increases in the lifespan of people living in developed nations. While infectious triggers of the immune system have clearly diminished in the last centuries, non-infectious triggers of the immune and metabolic systems, in the form of man-made bioactive substances, pollution, smoking and other stressors, have increased. It is becoming increasingly evident that our immune and metabolic systems respond to the Western lifestyle with chronic, low-grade inflammation, also called metaflammation, as well as increased reactivity of immune cells in many organs. Metaflammation is now thought to be causally linked to the development of many non-communicable diseases (NCD) of the aging modern societies.

In the SFB Metainflammation we will assist biologists and physicians to unravel the molecular basis of metainflammation and to develop strategies to reverse it. As the central computational biology unit, we will interact with over 20 subprojects and work on data analysis, integration and modeling.

Job description:

  • Data management, statistical analysis and machine learning for large datasets (e.g. single-cell omics, high-throughput and patient data)

  • Development of statistical inference and machine learning methods

  • Interpretation of analysis results

  • Statistical and bioinformatic consulting

  • Collaboration with biologists and medical researchers

  • Publication of scientific results at conferences and in journals

  • Co-supervision of students

Your profile:

  • PhD degree in (bio-)informatics, computational biology, computer science, mathematics or equivalent

  • Strong experience in at least three of the following topics: Bioinformatics, statistics, machine learning, and data management/integration

  • Programming skills (e.g., R or Python)

  • Proficiency in written and spoken English

  • Passion for science and scientific work

Our offer:

  • Working in an innovative, well-equipped and scientifically stimulating environment

  • Further training opportunities

  • Initial fixed-term employment contract for 3 years with a standard public service salary (PostDoc: 100% TV EntgO Bund EG 13)

The deadline for the application round is March 30, 2021.

Application documents (cover letter, CV, certificates, two reference letters) should be submitted as soon as possible as a single PDF file via email.

Contact: Prof. Dr. Jan Hasenauer, [Email protection active, please enable JavaScript.]

PhD in Biomedical Imaging

Biomedical Imaging is becoming increasingly important in modern medical research. Many novel imaging methods (for example in radiology or cardiology) are based on machine/deep learning. However, in many cases, a rigorous mathematical analysis of these techniques is lacking.

In this project, we will develop novel (learning-based) image reconstruction/analysis approaches for problems in immunology and radiology. Here, we are particularly interested in a precise mathematical formulation, quantification of uncertainty, development of efficient optimization algorithms, and final implementation using state-of-the-art programming languages and frameworks (primarily Python (PyTorch) and/or C++ (CUDA)). A close collaboration with the Institute for Applied Mathematics, the University Hospital Bonn, and the Clusters of Excellence Hausdorff Center for Mathematics and ImmunoSensation is intended.

Job description:

  • Development and mathematical analysis of novel reconstruction and shape space methods for (biomedical) imaging
  • Implementation of methods for high-performance computing (HPC) infrastructures
  • Application of methods to immunology and radiology (e.g. reconstruction/analysis of microscopy data (light sheet fluorescence, two-photon excitation, ...) or radiological images)
  • Collaboration with national and international partners

Your profile:

  • Master degree in mathematics, computer science or equivalent
  • Background in numerical optimization, variational methods, image processing, partial differential equations, (discrete) Riemannian geometry, or machine learning
  • Programming experience (Python/PyTorch and/or C++/CUDA)
  • Proficiency in written and spoken English
  • Passion for science and scientific work

Our offer:

  • Working in an innovative, well-equipped and scientifically stimulating environment
  • Further training opportunities
  • Initial short-term employment contract for 3 years with a standard public service salary (TV-L EG 13, 75%)

The deadline for the application round is March 30, 2021.

Application documents (cover letter, CV, certificates, two reference letters) should be submitted as soon as possible as a single PDF file via email.

Contact: Prof. Dr. Alexander Effland, [Email protection active, please enable JavaScript.]

Document Actions