Post-Doc researcher: Algorithm design to accelerate cognitive applications based on Big Data

Ref. 2016-20

Project description

We are looking for a post-doc researcher at IBM Research – Zurich in the Foundations of Cognitive Solutions group.

The candidate will work on new algorithms based on approximation and complexity reduction for Big Data analytics, deep learning, as well as potentially large classical HPC applications based on PDEs. These algorithms will be designed to run on new experimental hardware platforms, where accuracy has been partially traded off for extremely higher energy efficiency, as well as on more classical architectures.

The target is to reduce drastically the costs of real-world industry problems and improve the efficiency of existing and future IBM cognitive computing solutions.

During the post-doc period, the person will have the opportunity to acquire experience in several areas, publish in major international journals, learn how to patent his/her best new ideas, as well as deal with clients and real business cases.


Candidates must have a strong background in Computer Science, Mathematics, Physics, or equivalent, with an outstanding university track record.

We expect strong analytical and problem-solving skills, solid programming skills in C++ and Python (or similar), ability to conduct independent research, as well as excellent communication and team skills.

Experience with software engineering GPU programming, familiarity with machine learning, Big Data analytics, graph analytics and deep learning are all plus.


IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent flexible working arrangements enable both women and men to strike the desired balance between their professional development and their personal lives.

How to apply

Interested candidates, please send your application including CV and motivation letter to Dr. Cristiano Malossi.

Applicant review will begin immediately.

Administrative Contract Specialist

Ref. 2016-19

IBM Research GmbH is the leading ICT research organization in Switzerland. We are driving a strong network of partnerships with academic and commercial organizations mainly in Europe but reaching around the globe.

We are looking for an

Administrative Contract Specialist 100%

to manage the contracts administration for our research laboratory. After some training you will be handling standard contracts with the support of our contract negotiators and lawyers. We are a small team looking for a colleague who will own our contract management system and thus provide a key service to our researchers who are collaborating with external partners.

You have a commercial education with a paralegal background, a structured working style and a strong interest in contractual and legal matters. You are proactive, solution-oriented, service-focused and a self-starter. You have an open and collaborative personality, and you like to work in a team. Your profile is rounded off with excellent English and German skills.


IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent flexible working arrangements enable both women and men to strike the desired balance between their professional development and their personal lives.

Mirjam Strebel would be delighted to receive your application by email.

Note that we consider only direct applications. Applications sent through employment agencies will not be accepted.

Post-Doc researcher: Foundations of Cognitive Solutions

Ref. 2016-18

Project description

We have an opening for a post-doctoral research position in our Foundations of Cognitive Solutions group.

The opening is in the context of the IBM Watson ecosystem with a focus on large-scale, cloud-related aspects of visual scene segmentation, object recognition and semantic mapping. The successful candidate will research and implement novel efficient methods for semantic data representation as well as data processing to aid machine cognition and human–machine interaction.


The ideal candidate has a degree in Robotics (including Computer Science, Electrical Engineering, or similar fields), with a track record in simultaneous localization and mapping (SLAM) as well as computer vision related to robotics.

The ideal candidate demonstrates strong programming skills (C++; familiarity with relevant libraries and toolboxes such as ROS, OpenCV, etc), the ability to conduct independent research, to work in a team and to assume responsibility.


IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent, flexible working arrangements enable both women and men to strike the desired balance between their professional development and their personal lives.

How to apply

Interested candidates, please send your application including CV and cover letter to

Dr. Martin Rufli

+41 44 724 8714

Applicant review will begin immediately.

3 PhD positions: NeMeCo - Near-memory computing - Scaling big-data processing into the next decade

Ref. 2016-16

Project description

The emerging knowledge economy relies increasingly on big-data applications to extract value out of huge amounts of data by searching for correlations that can be used to predict business trends, find the best medical treatment for diseases, perform financial risk management, determine the best locations to drill for oil and gas, fight crime, and for many other purposes. Big-data applications are very different from traditional workloads and put extremely high demands on the High Performance Computing (HPC) systems that are used to execute them.

One of the key challenges in designing new generations of HPC systems that can keep up with the ever-growing data volumes, is that current technological trends prevent large amounts of data to be transferred at acceptable power dissipation costs. Reducing expensive data transfers by “bringing computation closer to the data”, also known as near-memory computing, has emerged as a very promising solution to address this scaling issue in HPC systems in order to realize the Exascale computing systems that are required for handling future Big-data workloads. Near-memory computing, however, is still in its infancy, and many challenges have to be addressed before it can be established as an integral component of HPC systems.

NeMeCo is an ambitious Marie Skłodowska-Curie European Industrial Doctorates (EID) Innovative Training Network (ITN) programme, which addresses several of the above challenges. In particular, NeMeCo is an interdisciplinary training and research project aimed at developing power-efficient HPC systems for Big-data processing based on the exploitation of near-memory computing capabilities, and, in this way, making the world a better place by enabling important innovations in, for example, healthcare, energy consumption, traffic congestion and safety.

NeMeCo involves a three-partner network comprising the Eindhoven University of Technology in the Netherlands, IBM Research - Zurich, and the Netherlands Institute for Radio Astronomy, ASTRON. These partners provide a unique combination of academic and industrial expertise of Big-data applications, compilers, memory and processor technology, and high-performance computer architecture. NeMeCo offers early stage researchers (ESRs) an excellent multidisciplinary training program at the cross roads of hardware and software design, where complex trade-offs have to be made between performance, programmability and energy efficiency. A board of 8 experienced supervisors will work together across disciplines and sectors to train and mentor the ESRs who will have access to superb research facilities at all locations. A total of three individual PhD projects are available

These three projects complement each other to cover the wide spectrum of aspects related to the following research objectives that build upon each other:

  1. Analysis of Big data workloads, their key algorithms, their complexity in terms of memory, compute and I/O operations, their data locality, their parallelization potential, their mappings to various platforms, possible algorithmic optimizations, etc. The purpose is to obtain a detailed understanding of their characteristics, and their static and dynamic processing requirements (ESR1+2+3).
  2. Modelling of selected Big data workloads, modelling of conventional computer architectures and of potential novel architectures based on near-memory computing, and modelling of the mapping of the workloads on those architectures. Objective is to enable a huge design space exploration, but still with sufficient detail based on accurate predictions of power consumption and performance (ESR1+2+3).
  3. Development of techniques for partitioning, mapping, and compiling Big data workloads on a hybrid HPC system combining conventional processing elements with near-memory computing capabilities (ESR2). Development of techniques for run-time optimization of the performance and power consumption (ESR1). Development of a system-level and accelerator level architecture for a near-memory computing device integrated into a hybrid HPC system (ESR3).
  4. Realization of a near-memory computing tool set and ecosystem including compiler, debugger, performance analysis, and run-time optimization tools (ESR1+2), and a near-memory computing device implementation in a hardware description language (ESR3).
  5. Translation of the expertise, models, tools and architecture, into a small-scale demonstrator of a computing system supporting near-memory computing (ESR1+2+3). This demonstrator will be integrated into an emerging ecosystem for HPC technologies, which increases the commercial relevance of the developed near-memory computing tool set and architecture while, at the same time, allowing evaluation of its application to a wide range of real-world problems. The latter is a key element of the proposed cutting-edge research program and will be instrumental for realizing break-through innovations.

The training is structured individually for each ESR based on a personal career development plan which covers scientific, personal and transferable skills. The ESRs will be employed for an initial period of three years by the Eindhoven University of Technology in the Netherlands, which will also award the PhD degrees. If successful, the employment will be extended by a fourth year. Each ESR will do secondments at IBM Research GmbH in Switzerland (for about 20 months) and at ASTRON in the Netherlands (for about 4 months).

As part of the NeMeCo project, the three ESRs will have access to an exceptionally wide range of state-of-the-art server and supercomputing technologies, including an on-site BlueGene BG/Q system, a collection of OpenPOWER hardware, various commercial GPUs, FPGAs, and DSPs, as well as technologies that are not on the market yet, such as the world’s first hot water cooled 64-bit microserver and an accelerator platform that is based on the direct attachment of FPGAs to the memory interconnect of a commercial server processor.

In addition, the DOME project, in which ASTRON and IBM jointly perform fundamental research on large-scale green Exascale computing for the Square Kilometre Array (SKA) radio telescope, offers the ESRs a unique opportunity to get experience with an “extremely Big”-data application, involving the processing of Exabytes of astronomical data collected by hundreds of thousands of antennas and dishes for exploring the universe. The SKA will become the biggest radio telescope on earth requiring enormous compute power when it becomes operational in the next decade.

More information on the job requirements, conditions of employment, and how to apply

Download PDF of this job description

Post-Doc researcher: NLP and medical ontologies in German for cognitive pre-clinical assessment of patients

Ref. 2016-13

Project description

RHÖN and IBM will join forces to accelerate pre-clinical assessment of patients through cognitive computing built on top of our Watson capabilities. The goal is to equip doctors and medical staff with evidence and data insights before the patient even enters the clinical phase. This will result in improved medical care during pre-clinical assessment both for ambulant and inpatient care so that the right patient receives the right treatment at the right time.

In this context we are looking to hire a Post-Doctoral Fellow into our research team. We look for an enthusiastic person skilled in Natural Language Processing and medical ontologies in German, who is capable of programming and keen on taking up new tools and approaches. We very much work in a team where each member complements the others. The work will have a direct impact on the client as well as on research in healthcare informatics.

In the future, RHÖN‐KLINIKUM AG, one of the largest healthcare providers in Germany, will cooperate with IBM in order to optimise patient management. The concept of the joint project is to ensure data-assisted patient navigation providing the best possible healthcare at the pre-clinical stage already and subsequently moving into either the in-patient or out-patient treatment. Inappropriate patient referrals, which cost both time and money, can therefore be avoided. Better use of patient data can also help in providing further recommendations for treatment.

IBM will contribute innovative “cognitive computing“ technology to this joint project. In a first phase, a cognitive assistance system will be installed at the “Center for Undiagnosed and Rare Diseases” at the university hospital in Marburg to help in the very work-intensive processing of such medical cases. The IBM Research – Zurich Laboratory will be responsible for the technological management of the project. The knowledge obtained from the first project phase at the university hospital in Marburg will then be analyzed and used for other hospitals in the corporate group.


IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent, flexible working arrangements enable both women and men to strike the desired balance between their professional development and their personal lives.


Matthias Reumann, PhD
Sustainable, resilient health systems research
IBM Research – Zurich
Saeumerstrasse 4, 8803 Rueschlikon, Switzerland
office: +41 44 724 84 12
mobile +49 157 313 867 43

Master's thesis project in Systems Biology group: Spatiotemporal modelling of DNA replication

Ref. 2016-12

Project description

DNA replication, the duplication of a cell’s genetic material, ensures the maintenance of the genetic information and is the basis of biological inheritance. In eukaryotic cells, DNA replication initiates at multiple locations in the genome, known as origins of replication, and continues from there in both directions, thereby creating replication forks.

This project aims at developing a stochastic hybrid model of DNA replication that incorporates spatial information on origin locations and protein mobility dynamics. The ultimate goal is to understand the relationship between 3D structure and DNA replication. The model will be tailored for the case of fission yeast using recent experimental data and will be simulated in a high-performance computing setup.

The research will be conducted in collaboration between the Automatic Control Laboratory of ETH Zurich and IBM Research – Zurich. More specifically, the project will involve:

  • Adapting an existing model of protein mobility [1, 2] for the case of fission yeast nucleus and model origin locations in 3D using experimental data.
  • Integrating the origin location and existing DNA replication models [3] to enable stochastic initiation of origin firing when activation factors diffuse and bind onto the origins.
  • Simulating the resulting integrated model to test various hypotheses, for example different kinetic parameters of the activation factors or different relative positioning of the origins.
  • Examining whether and how relative origin positioning affects replication timing and how the process is affected by the dynamics of activation factors.


IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent, flexible working arrangements enable both women and men to strike the desired balance between their professional development and their personal lives.


For more information please contact J. Lygeros and M. Rapsomaniki.


[1] E. Cinquemani, V. Roukos, Z. Lygerou, and L. Lygeros,
"Numerical analysis of FRAP experiments for DNA replication and repair," in IEEE Conference on Decision and Control, Cancun, Mexico, December 9-11, 2008. 
[2] M. Rapsomaniki, E. Cinquemani, N. Giakoumakis, P. Kotsantis, J. Lygeros, and Z. Lygerou,
"Inference of protein kinetics by stochastic modeling and simulation of fuorescence recovery after photobleaching experiments," Bioinformatics 31(3) 355-362, 2015. 
[3] J. Lygeros, K. Koutroumpas, S. Dimopoulos, I. Legouras, P. Kouretas, C. Heichinger, P. Nurse, and Z. Lygerou,
"Stochastic hybrid modeling of DNA replication across a complete genome," Proceedings of the National Academy of Sciences of the U.S.A., vol. 105, pp. 12295-12300, August 2008. 

Post-Doc researcher: Developer of computational methods to support personalized medicine in cancer

Ref. 2015-18

Project description

A postdoctoral research position is available at IBM – Zurich Research Laboratory to develop computational methods to support personalized medicine in cancer. This highly interdisciplinary project involving the collaboration of several institutions across Europe and USA will focus on prostate cancer, a leading cause of cancer death amongst men, but also prone to over-treatment.

Maria Rodrigues Martinez on working in SwitzerlandThe project aims to develop computational models that can exploit molecular and clinical data in order to improve our understanding of cancer disease mechanisms and predict optimized strategies for therapeutic intervention. The models will be based on the exploitation of genomic, transcriptomic, proteomic, and clinical data in primary and metastatic tumors, prospective cohorts of well characterized prostate cancer patients, drug screenings in cell lines, and the use of the Watson technology, a last-generation cognitive computer developed at IBM.

The successful candidate will analyze molecular data in order to characterize tumor heterogeneity, and will develop methodologies to integrate disparate types of data into models that can help risk-stratify patients.


Candidates should have a strong background in computer science, mathematics or physics and be interested in cancer-related research. Strong programming skills are necessary. Experience in machine learning, Big Data analysis, and high-performance computing is a plus.

About the group

The group of systems biology at IBM aims to develop new mathematical and computational approaches for the analysis and exploitation of the latest generation of biomedical data. In the context of cancer, the group focuses on the integration of high-throughput molecular datasets to build comprehensive molecular disease models; the development of new approaches to reconstruct signalling protein networks from single-cell time-series proteomic data; and the application of Bayesian approaches and high-performance computing to the problem of network reconstruction.


IBM is committed to diversity at the workplace. With us, you will find an open, multicultural environment. Excellent, flexible working arrangements enable both women and men to strike the desired balance between their professional development and their personal lives.

How to apply

Interested candidates, please send an application including CV and reference letters to:

Systems biology

Maria Rodrigues Martinez on working in SwitzerlandWe support motivated candidates who are willing to apply for competitive personal fellowships. Interested candidates please contact .

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