Computational Statistician

Center for Biosustainability
Wednesday 26 Sep 18

Apply for this job

Apply no later than 22 October 2018
Apply for the job at Center for Biosustainability by completing the following form.

Apply online

Quantitative Modelling of Cell Metabolism (QMCM) is a new section at the Novo Nordisk Foundation Center for Biosustainability, headed by Professor Lars Keld Nielsen and supported by a seven year Novo Nordisk Foundation Laureate Research Grant. In QMCM, we focus on developing mathematical models and computational to explore and explain the molecular basis for homeostasis – the self-regulating processes evolved to maintain metabolic equilibrium in organisms.

Studying homeostasis is relevant for the understanding and treatment of complex diseases, particular with the emergence of personalized medicine. It is equally important when we seek to repurpose the cellular machinery of microbes for the production of desired chemicals, materials and pharmaceuticals. In this process, the cells’ homeostatic control mechanisms must be either disabled or exploited. The ultimate aim is to be able automatically to convert the omics “parts” lists (genome, transcriptome, proteome, metabolome) now routinely collected for many individuals into accurate and simulatable models to guide treatment and design.

Cellular reactions are catalyzed by enzymes. In order to model homeostasis, we need to model the kinetics of all the enzymes involved in cellular metabolism. We can generally assume the system is in pseudo-steady state governed by the steady state mass balance equation: Sv(s;p,x)= 0, where S is a known stoichiometry matrix defining what is produced/consumed by each reaction, v is a set of rational functions describing the kinetics of each reaction (may be 80-200 reactions in the final model), s are the steady state metabolite concentrations, p are the kinetic parameters (5-20 per reaction), x are measured system variables with an error associated (concentration of enzymes, boundary metabolites, boundary fluxes). For a given set of parameters (p,x), the equation has a unique solution (s,v) so that Sv = 0 and we have measurements of at least a subset of (s,v) to compare the solution against.

This is an opportunity for a computational statistician with expertise in Bayesian statistical inference to join an interdisciplinary team working on biological network modelling, computer science and algorithmics, statistical computation and bioinformatics, to solve the fundamental challenge of formulating and fitting very large non-linear models.

Responsibilities and tasks
As a member of the multi-disciplinary team, you will contribute your expertise towards developing statistical computation solutions for large, non-linear problems. In particular, you will enable the team by building the necessary statistical software tools and pipelines.
Examples of the challenges you will address include:
  • Working with modellers and software engineers in QMCM to develop an efficient translation of physical model formulation into a computational Bayesian model;
  • Independently develop high-quality and maintainable software under the Stan framework necessary to solve the problem, e.g., efficient GPU utilisation and implicit function solvers.
The incumbent must be able to spend extended periods of time at Aalto University, Finland, to develop Stan programs under the guidance of Associate Professor Aki Vehtari. The incumbent may also need to occasionally visit Columbia University to work with the core team of Stan developers.

Candidates should have a PhD degree or equivalent.
  • You have expertise in computational statistics
  • You write high-quality, structured and maintainable code.
  • You are an expert in at least one of the following programming languages and their associated scientific software stacks and generally comfortable dealing with one or two others: C++, R, Python, Julia.
  • You have extensive experience with advanced statistical computation platforms, preferably Stan.
  • You are at ease working in teams as well as working independently.
  • Experience with machine learning and GPU computing is a plus.
  • Experience with MPI and/or openMP is a plus.
  • Experience with Docker and other similar virtualization technologies (especially in the context of scientific computing) is a plus.

What we offer in return
We offer an interesting and challenging job in an international atmosphere with the focus on research, teaching, innovation and scientific advice for the benefit of the surrounding community. We place emphasis on a high level of professionalism among our staff, so skills development is an integral part of our organization. We offer a great flexibility in the position. In the area of technical and natural sciences, DTU is one of the leading research and education institutions in Europe.

Salary and terms of employment
The appointment will be based on the collective agreement with the Confederation of Professional Associations. The allowance will be agreed with the relevant union.
Workplace and period of employment:

You will be based in the recently opened, custom-designed DTU Biosustain building at the DTU Lyngby Campus

The period of employment is 3 years.

Application procedure and contact
Please submit your online application no later than 22 October 2018.
Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online," fill in the online application form, and attach all your materials in English in one PDF file. The file must include:
  • Application (cover letter)
  • CV
  • Diploma (MSc/PhD)
  • List of publications 
Applications and enclosures received after the deadline will not be considered.

Further information may be obtained from Scientific Director Lars Keld Nielsen,
You can read more about The Novo Nordisk Foundation Center for Biosustainability on
All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.

DTU Biosustain is an international research center of excellence developing next generation cell factories and bioprocesses for sustainable production of high-value chemical compounds as well as protein-based products. The center uses advanced metabolic engineering techniques and computational biology ensuring efficient and cost-effective design and construction processes.

The center’s activities are a balanced mix of basic and translational research, complemented by an emphasis on business development to facilitate commercialization of new cell factories and associated technologies. DTU Biosustain offers state-of-the-art research facilities and assembles world leaders in the field thus offering a unique platform providing excellent talent development and career opportunities.

DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 6,000 advance science and technology to create innovative solutions that meet the demands of society, and our 11,200 students are being educated to address the technological challenges of the future. DTU is an independent academic university collaborating globally with business, industry, government and public agencies.