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

PhD student in Applied Mathematics and Computational Biology (focusing on Statistical Inference for Dynamical Systems)

The University of Bonn is an internationally operating research institution, with 200 years of history, around 38,000 students, more than 6,000 employees and an excellent reputation at home and abroad: the University of Bonn is one of the most important universities in Germany. In the last excellence initiative, the University of Bonn was able to secure six Clusters of Excellence, more than any other German institution, for research topics including mathematics and immunology. 

In this excellent scientific environment, our research group (https://www.mathematics-and-life-sciences.uni-bonn.de/en) develops and applies novel mathematical approaches and software tools for data analysis and modeling. The spectrum of applications spans oncology, immunology, and epidemiology. We are intensively collaborating with world-leading experts for mathematics, immunology and neurology. Currently, we are searching for multiple PhD students and Postdocs to complement our interdisciplinary team. 

Statistical inference for dynamical systems has applications in many different fields, including systems biology, economic modelling, epidemiological modelling, and physics-inspired simulations. The PhD student will develop a research project with broad flexibility in the topic. Possible topics include the development of methods in parameter estimation or other parts of model calibration, such as uncertainty quantification methods or model selection algorithms. With the group's close connections to LIMES and the UKB, the PhD student will have access to collaborations with experimentalists, to apply statistical inference methods to real world problems. 

Job description: 

  • Data management and statistical analysis of biological data (e.g., single-cell omics, high-throughput histology and patient data) and/or 

  • Mathematical modeling of biological processes (incl. ordinary and partial differential equations, stochastic models) and/or 

  • Development of statistical inference and machine learning methods. 

  • Interpretation of analysis results. 

  • Collaboration with biologists and medical researchers. 

  • Publication of scientific results at conferences and in journals.  

  • Assistance with teaching and trainings (e.g., in mathematics or computer sciences). 

Your profile: 

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

  • Experience in some of the following fields: mathematical modelling (e.g., ODEs and PDEs for biological processes), numerical optimization, machine learning, bioinformatics, and high-performance computing 

  • Programming skills (preferably Python or C++) 

  • Proficiency in written and spoken English 

  • Passion for science and scientific work 

Our offer: 

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

  • An international and diverse group of PhD students and Postdocs 

  • A professional career development program for both PhD students and Postdocs 

  • Initial contract for 3 years with a standard public service salary (PhD student: 75% TV-L EG 13; PostDoc: 100% TV-L EG 13; Scientific software developers: 100% TV-L EG 13) 

The University of Bonn is committed to diversity and equal opportunity. It is certified as a family friendly university. It aims to increase the proportion of women in areas where women are under-represented and to promote their careers in particular. It therefore urges women with relevant qualifications to apply. Applications will be handled in accordance with the Landesgleichstellungsgesetz (State Equality Act). Applications from individuals with a certified serious disability and those of equal status are particularly welcome. 

The deadline for the application round is March 15, 2022. Application documents (cover letter, CV, certificates, contact details of two referees) 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 or PhD student in Mathematics and Machine Learning (focusing on infectious disease modeling)

Host-pathogen interactions determining the outcome of infections are complex biological processes, governed by the interplay of diverse factors across multiple spatial and temporal scales. While data (e.g. from imaging, serology, multi-omics) are becoming available at an unprecedented level of detail, their integration and interpretation is challenging. Computational models, e.g. using differential equations or hybrid discrete-continuous descriptions, facilitate a mechanistic understanding, and are used to study e.g. the response of individuals to virus infections and vaccinations, or the interplay of pathogens and immune cells. However, statistical inference for such models is computationally demanding and does not scale to the steadily growing datasets from large clinical cohorts and high-throughput technologies.

In this project, set in the context of the BMBF project EMUNE, we build a framework for scalable statistical inference of host-pathogen interactions, combining novel concepts from machine learning with mechanistic modeling. Specifically, we develop methods based on invertible neural networks (INN) to describe probabilistic parameter-data relationships, for large but incomplete datasets. Based on these, we develop scalable marginalization and inference methods for non-linear mixed-effect (NLME) models. We apply these models to large-scale epidemiological datasets, e.g. from the pan-European SARS-CoV-2 study ORCHESTRA.

 Job description:
  • Development of statistical inference and machine learning methods, with focus on non-linear mixed-effect models and invertible neural networks
  • Implementation of algorithms in open-source, reusable software packages
  • Application of methods to biological data, with focus on infectious diseases such as SARS-CoV-2 and HIV
  • Publication of results in scientific journals and at conferences
  • Collaboration with national and international partners
  • (As PostDoc) Co-supervision of students and assistance with teaching
Your profile:
  • Master / PhD degree in (bio-)informatics, computational biology, computer science, mathematics, physics, or a related field
  • Experience in some of the following fields: mathematical modeling, mixed-effect modeling, differential equations, statistical inference, numerical optimization, machine learning
  • Programming skills in e.g. Python, Julia, C++, or R, and collaborative software development experience
  • Proficiency in written and spoken English
  • Passion for science and scientific work
 Our offer:
  • Working in an innovative, well-equipped and scientifically stimulating environment
  • An international and diverse group of PhD students and PostDocs
  • A professional career development program for both PhD students and PostDocs
  • As PhD student, initial 3 year contract with a standard public service salary (75% TV-L EG 13); as PostDoc initial 2 year contract (100% TV-L 13)
  • PostDocs will have opportunities to obtain additional external funding and develop an independent research program during postdoctoral training
  • Further training opportunities
The deadline for the application round is March 15, 2022.

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-L EG 13)

The deadline for the application round is March 15, 2022.

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 Bioinformatics (focusing on systems energetics)

A central physiological process - energy homeostasis - regulates the energy balance within the body. An energy imbalance can have severe consequences on health and has led to the obesity pandemic with approximately two billion overweight people world-wide. This in turns leads to a substantially-increased risk for common chronic and fatal illnesses including type 2 diabetes, cardio-vascular diseases and cancer.

In the CRC/TRR Brown and Beige Fat an internationally-coordinated research consortium of renowned and leading experts in the field of energy metabolism (and systems energetics) strive to shed light on the cascade of organ crosstalk, signaling and energetics in close collaboration with computational biologists, bioinformaticians and physicians. As the central data computational unit, we will conduct research with 17 project partners from the life and medical sciences and make use of and establish data analysis and integration as well as mechanistic modelling to unravel underlying biological function. 

Job description:
  • Data management, statistical analysis and machine learning for large datasets (e.g. cell line models, mouse models and patient data)
  • Development of a causal modelling pipeline based on natural language processing to assist the project partners in hypothesis generation (cell-cell and organ-organ crosstalk)
  • Interpretation of analysis results and assist with reproducible computational analysis
  • Statistical and bioinformatic consulting
  • Collaboration with biologists and medical researchers
  • 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

Demonstrated proficiency in deep learning frameworks e.g. pyTorch or TensorFlow and/or parallel distributed processing approaches such as MapReduce or Hadoop Spark beneficial.

 
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-L EG 13)
The deadline for the application round is March 15, 2022.

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 Systems Biology (focusing on federated analysis of COVID-19 clinical data)

The EU project ORCHESTRA provides an innovative approach to learn from the COVID-19 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, taking into account not only epidemiological, clinical, microbiological, and genotypic aspects of the population, but also environmental and socio-economic factors. 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) composed by SARS-CoV-2 infected and non-infected individuals of all ages and conditions. The main contribution of ORCHESTRA will be 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 COVID-19. 

Carrying out the analysis of such a large-scale, multi-center data set requires overcoming several challenges. The most limiting factor is the legal impossibility of sharing and collecting in a single location all the data due to privacy concerns. We will utilize federated learning techniques, which allow the statistical analysis of distributed data without individual-level information ever being directly accessible to the analyst. In contrast to standard meta-analysis techniques, the results of a federated analysis are equivalent (or practically so) to a pooled analysis. Due to its novelty, algorithms and software for federated learning are still few. We will thus need to take known methods from machine learning and statistical analysis, as well as (fine-grained) dynamical models, and adapt them to a federated framework.

Job description:

  • (Federated) statistical analysis and machine learning for the analysis of a large-scale, multi-center COVID-19 data set in order to study factors relevant to the infection and disease severity for acute- and long-COVID

  • Interpretation of analysis results
  • Collaboration with biologists and medical researchers
  • Publication of scientific results at conferences and in journals
  • Assistance with teaching and training (e.g., in mathematics or computer sciences)
  • Co-supervision of students

Your profile:

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

  • Strong experience in some of the following topics: Bioinformatics, statistics, mathematical modeling (e.g., ODEs and PDEs for biological processes), machine learning, and data management/integration
  • Programming skills (preferably R and/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 
  • An international and diverse group of PhD students and Postdocs
  • A professional career development program
  • Opportunities to obtain additional external funding and develop an independent research program during postdoctoral training.
  • Initial fixed-term employment contract for 2 years with a standard public service salary (PostDoc: 100% TV-L EG 13)

The University of Bonn is committed to diversity and equal opportunity. It is certified as a family friendly university. It aims to increase the proportion of women in areas where women are under-represented and to promote their careers in particular. It therefore urges women with relevant qualifications to apply. Applications will be handled in accordance with the Landesgleichstellungsgesetz (State Equality Act). Applications from individuals with a certified serious disability and those of equal status are particularly welcome.

The deadline for the application round is March 15, 2022.

Application documents (cover letter, CV, certificates, contact details of two referees) 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 student in Systems Biology (focusing on federated analysis of COVID-19 clinical data)

The EU project ORCHESTRA provides an innovative approach to learn from the COVID-19 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, taking into account not only epidemiological, clinical, microbiological, and genotypic aspects of the population, but also environmental and socio-economic factors. 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) composed by SARS-CoV-2 infected and non-infected individuals of all ages and conditions. The main contribution of ORCHESTRA will be 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 COVID-19.

Carrying out the analysis of such a large-scale, multi-center data set requires overcoming several challenges. The most limiting factor is the legal impossibility of sharing and collecting in a single location all the data due to privacy concerns. We will utilize federated learning techniques, which allow the statistical analysis of distributed data without individual-level information ever being directly accessible to the analyst. In contrast to standard meta-analysis techniques, the results of a federated analysis are equivalent (or practically so) to a pooled analysis. Due to its novelty, algorithms and software for federated learning are still few. We will thus need to take known methods from machine learning and statistical analysis, as well as (fine-grained) dynamical models, and adapt them to a federated framework.

Job description:

  • (Federated) statistical analysis and machine learning for the analysis of a large-scale, multi-center COVID-19 data set in order to study factors relevant to the infection and disease severity for acute- and long-COVID

  • Programming (Python or R)
  • Interpretation of analysis results
  • Collaboration with biologists and medical researchers
  • Publication of scientific results at conferences and in journals
  • Assistance with teaching and training (e.g., in mathematics or computer sciences)
Your profile:
  • Master degree in (bio-)informatics, computational biology, computer science, mathematics or equivalent
  • Experience in some of the following topics: Bioinformatics, statistics, mathematical modeling (e.g., ODEs and PDEs for biological processes), machine learning, and data management/integration
  • Programming skills (preferably R and/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 
  • An international and diverse group of PhD students and Postdocs
  • A professional career development program
  • Initial fixed-term employment contract for 3 years with a standard public service salary (PostDoc: 75% TV-L EG 13)
  • The University of Bonn is committed to diversity and equal opportunity. It is certified as a family friendly university. It aims to increase the proportion of women in areas where women are under-represented and to promote their careers in particular. It therefore urges women with relevant qualifications to apply. Applications will be handled in accordance with the Landesgleichstellungsgesetz (State Equality Act). Applications from individuals with a certified serious disability and those of equal status are particularly welcome.
    The deadline for the application round is March 15, 2022.
    Application documents (cover letter, CV, certificates, contact details of two referees) 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.]


Scientific software developer (ideally with a PhD degree)

Our research group (https://www.mathematics-and-life-sciences.uni-bonn.de/en) develops and applies novel mathematical approaches and software tools for data analysis and modeling (https://www.mathematics-and-life-sciences.uni-bonn.de/en/software). Our tools are used by a number of research groups. Currently, we are searching for a Scientific software developer (ideally with a PhD degree) to complement our interdisciplinary team. The successful candidate will contribute to the development of our tools for efficient numerical simulation and parameter inference, in particular to AMICI (https://github.com/AMICI-dev/AMICI).
 

Job description: 

  1. Development of tools for simulation of dynamical systems, statistical inference and machine learning. 

  2. Maintenance of software tools and improving documentation and usability

  3. Providing user support

  4. Publication of scientific results at conferences and in journals.  

Your profile: 

  1. (Ideally a PhD) degree in (bio-)informatics, computational biology, computer science, mathematics, physics, or related fields 

  2. Experience in some of the following fields: mathematical modelling (e.g., ODEs and PDEs for biological processes), numerical optimization, machine learning, bioinformatics, and high-performance computing 

  3. Solid programming experience in Python and C++

  4. Experience with version control systems and automated software testing

  5. Proficiency in written and spoken English 

  6. Passion for science and scientific work 

Our offer: 

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

  2. An international and diverse group of PhD students and Postdocs 

  3. A professional career development program

  4. Initial contract for 2 years with a standard public service salary (100% TV-L EG 13)

The deadline for the application round is March 15, 2022. Application documents (cover letter, CV, certificates, contact details of two referees) should be submitted as soon as possible as a single PDF file via email. 

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



PhD student in Applied Mathematics

Our research group (https://www.mathematics-and-life- sciences.uni-bonn.de/en) develops and applies novel mathematical approaches and software tools for data analysis and modeling in the context of various diseases. Currently, we are searching for a PhD student in Applied Mathematics to complement our interdisciplinary team. The successful candidate will apply and develop methods for model-based analysis of biological data in the field of metabolic disorders.
 

Job description: 

  1. Analysis of biological data  (e.g., metabolomics, transcriptomics, clinical data, …) using mechanistic and statistical modeling and/or 

  2. Application and development of statistical inference and machine learning methods. 

  3. Interpretation of analysis results. 

  4. Collaboration with biologists and medical researchers. 

  5. Publication of scientific results at conferences and in journals.  

  6. Assistance with teaching and training (e.g., in mathematics or computer sciences). 

Your profile: 

  1. Master / PhD degree in (bio-)informatics, computational biology, computer science, mathematics, physics, or related fields 

  2. Experience in some of the following fields: mathematical modelling (e.g., ODEs and PDEs for biological processes), numerical optimization, machine learning, bioinformatics, biochemistry, and high-performance computing

  3. Programming experience, preferably in Python

  4. Proficiency in written and spoken English 

  5. Passion for science and scientific work 

Our offer: 

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

  2. An international and diverse group of PhD students and Postdocs 

  3. A professional career development program

  4. Initial contract for 3 years with a standard public service salary (75% TV-L EG 13)

The deadline for the application round is March 15, 2022. Application documents (cover letter, CV, certificates, contact details of two referees) should be submitted as soon as possible as a single PDF file via email. 

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




 

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