Master’s thesis: Cryogenic measurements and modeling of electrical devices

Ref. 2018-43

Project description

Liquid helium cryostat There is a growing need for electronics operating at cryogenic temperatures 4 K and below. Applications include space astronomy, physics experiments and, not least, quantum computers. Electronic circuits and devices such as amplifiers are cooled either for latency reasons, by facilitating tight integration with other circuitry, or to reduce the noise level they generate. There is thus a need to understand how the behavior and characteristics of such circuits and devices change as they are cooled to cryogenic temperatures. Not only can this help us design efficient electronics by predicting impedances and performance, but we may also find novel ways of using this change in behavior to our advantage.

In this Master’s thesis project, the aim is to examine the behavior of electrical devices, transistors and circuits as they are cooled to cryogenic temperatures. The project includes the following key elements:

  • Electrical measurements at cryogenic temperature, 4 K and above, of our inhouse transistor technology
  • Modeling of electrical behavior to understand the unique effects present at these temperatures
  • Both DC and high-frequency measurements

The Materials Integration and Nanoscale Devices (MIND) group has extensive experience in nanoelectronics research as well as cryogenic measurements, providing a strong infrastructure for a successful research project. The project is available immediately for a minimum duration of six months in a collaborative group at the IBM Research – Zurich laboratory.

Please note: This is a non-remunerated M.Sc. thesis project, not a funded position.

Requirements

  • Applicants are expected to pursue a Master’s degree in Engineering, Electrical Engineering, Physics or Nanoscience
  • Must be enrolled as a Master’s student at ETH Zurich
  • Experience with simulation or modeling would be a plus
  • Excellent English communication skills
  • Highly motivated, creative and independent.

Diversity

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, cover letter and academic transcript to: .

Post-doctoral researcher: Photonic recurrent neural networks

Ref. 2018-42

Project description

New computing paradigms bring the promise to extend the functionality of today’s Von Neumann based systems. Artificial intelligence and neural network based systems have proven to be good choices for the classification of unstructured data, image and speech recognition. To fully exploit the performance of such systems, dedicated hardware solutions will be required to accelerate neural network training and for fast and power efficient execution.

At IBM Research – Zurich we are establishing novel hardware technologies for neural networks by building on existing integrated electrical and optical platforms. Neural network simulations and system-level experiments complement the hardware-related activities and demonstrate the impact of the new technology platforms.

In the Neuromorphic Devices and Systems group, a post-doc position is available embedded in the SNF project NAPRECO, a collaboration with the University of St. Gallen (HSG). The main responsibility is to develop novel recurrent neural networks in the optical domain, benchmark such newly developed systems, and determine their applicability to real-world problems. The work will be at the interface between physical simulations and photonic characterization, mathematics of reservoir computing, and computer science.

Important tasks to be performed are:

  • Design of next-generation integrated photonic recurrent neural networks, interfacing with collaborators in the field of mathematics.
  • Developing an experimental setup to execute software-controlled training and interference tasks on the photonic hardware circuits.
  • Characterization and benchmarking of the recurrent neural networks fabricated in IBM cleanroom facilities.
  • Evaluation of newly developed hardware networks with common cognitive benchmarks and analysis of their applicability to real-world problems.

Duration

This post-doc position is for a duration of 18 months.

Requirements

Candidates with a strong background and interest in neural network-based systems, simulation of neural networks, and/or reservoir computing systems are encouraged to send their CV including publication list and references. Experience in the design and/or the high-speed characterization of optical systems is a plus.

Diversity

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

For more information please contact Dr. Bert Offrein at the address indicated below. Applications should be sent by email to , preferably before 20 December 2018.

Dr. Bert Jan Offrein
Manager Neuromorphic Devices and Systems
Phone: +41 44 724 8572
e-mail: ofb@zurich.ibm.com

Software Engineer

Ref. 2018-41

Environment

We are looking for an experienced and highly motivated software engineer to join the Cognitive Computing & Industry Solutions department at IBM Research – Zurich. Software engineers contribute to the architecture definition and implementation of our projects, which cover diverse subject areas, e.g., healthcare, medical image processing and systems biology. In the context of these projects, we use — and very often develop — novel tools for cognitive systems in areas including natural language processing (NLP), machine learning (ML) and knowledge representation (KR). The department has a large group of scientists and researchers with deep expertise and knowledge in these areas, who work together with our software engineers to develop prototype and production systems. Given that such results are frequently developed with (or for) industry partners, software quality, modularity, maintainability, scalability, security, and resilience are of paramount importance in the development process.

Software engineer role

We are looking for a software engineer for overall software design and implementation. This position requires someone with a strong personal drive and a hands-on attitude to analyzing requirements and potential solutions, discussing alternatives with the team, then leading the implementation and organizing the work so it can be distributed judiciously and executed among the team members. The successful candidate will also make a significant contribution to the implementation work and be responsible for tools and infrastructure used by the team in developing the solution.

Required skills

Candidates applying for this position should fulfill the following requirements:

  • Degree in Computer Science, Software Engineering, Software Architecture, or equivalent.
  • At least two years of industry experience in software-related positions.
  • Experience in applying standard software development methodologies.
  • A strong working knowledge of standard DevOps technologies such as GIT/CI/Docker is essential.
  • Ability to design a software architecture that achieves the goals of the project without overdoing it.
  • Full-stack development profile (web, database, server components).
  • Experience in testing, debugging, issue tracking and overall quality management.
  • Ability to document the system and set documentation guidelines for the team.
  • Ability to set up and maintain the infrastructure (HW, VMs) and tools required for the project.
  • Experience in working with customers to develop requirements and discuss technical aspects of the project.
  • Strong verbal and written communication skills in English.

Diversity

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

Please send your application documents by email to , Human Resources. Besides your CV, we kindly ask you to describe in your cover letter how you fulfill the position requirements. Please also indicate which other additional skills you possess that you consider relevant to the application process.

Research Staff Member / Post-doctoral researcher: Machine learning & AI explainability

Ref. 2018-19

About the position

The AI for Industries group at IBM Research – Zurich is working on cutting-edge AI research and applications to transform businesses across industries. We are working on deep-learning methods for predictive analytics and on explaining our predictions. We are looking for a person to join our effort on explainable AI and deep neural networks. The type of position (post-doctoral research or Research Staff Member) will depend on the person’s expertise.

The successful candidate is passionate about advancing science and creating the next generation of AI solutions. The person will have the opportunity to work in a collaborative and creative group, and participate in high-impact projects for large-scale, real-world industrial problems.

Required expertise

  • PhD in Computer Science, Machine Learning, Artificial Intelligence, or related technical fields
  • Strong programming skills in Python
  • Experience with standard machine-learning techniques and frameworks, including but not limited to TensorFlow, Keras, scikit-learn or PyTorch
  • Experience in working with time and event series data
  • Ability to conduct independent research
  • Excellent communication and team skills
  • Strong publication record in venues such as AAAI, ICLR, ICML, IJCAI, NIPS.

Desired expertise

  • Knowledge of big-data processing frameworks (e.g., Spark stack)
  • Knowledge of Scala programming language.

Diversity

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

If the above position fits your background, please send your complete CV, including a list of publications and skills, as well as contact information for three references to:

Student internship: Un-/Semi-supervised machine learning for real-time streaming analytics

Ref. 2018-21

About the internship

Analysis of continuous and discrete valued multivariate time series is essential for intelligent management of complex systems in a range of industries, from IT equipment to cash machines and wind turbines. In the context of storage systems, detecting anomalous behavior in nonstationary multivariate time series sensor data in real time can provide service teams the ability to identify impeding performance issues in a proactive manner and act accordingly before the customer experiences them. We plan to apply state-of-the-art techniques to analyze streaming time series for hundreds of sensors to identify and locate anomalies across correlated metrics, even when they are deeply hidden in high-dimensional subspaces. We are looking for an intern with a relevant background to join us in developing a big data anomaly-detection pipeline.

The successful candidate will have the opportunity to participate in an advanced machine-learning project that aims for high business impact by detecting and (potentially) predicting performance anomalies in managed storage systems. Additionally, the candidate will gain valuable experience in processing large quantities of data to create actionable insights.

Requirements

Candidates are expected to have the following background and interests:

  • Hands-on data science on the prevalent platforms, as well as the basic fundamentals of machine learning
  • Proficiency in Python
  • Experience with anomaly-detection techniques would be a plus
  • Familiarity with big-data technologies such as Spark would be a plus.

Diversity

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

If the above position fits your background and interests, please send your complete CV as well as contact information for three references to:

PhD student position: H2020 HELICAL consortium

Ref. 2018-39

About the position

A PhD research position is available at IBM Research – Zurich Laboratory as a part of the H2020 HELICAL consortium, which is focused on understanding rare autoimmune diseases.

Background

Humans are affected by approximately 100 distinct autoimmune diseases, which are caused by a breakdown in immune tolerance to self-antigens. In recent years, large amounts genomic, epigenetic, transcriptomic and clinical datasets, as well as environmental and epidemiological datasets from patients with chronic diseases have been produced and archived. Advances in information science and artificial intelligence provide unprecedented opportunities for using these datasets to elucidate the complex biology of these disorders, how they are influenced by environmental triggers, and how to personalize their management. HELICAL is an Innovative Training Network (ITN) that will focus on autoimmune vasculitis, a rare autoimmune disease, and will apply informatics to such datasets to gain new biological insights and translate new biological insight into practical clinical outputs.

Clinical challenge

The key clinical challenge in caring for people with vasculitis is balancing immune system inhibition, which is required to control the disease, against over-suppression, which can lead to a risk of death and morbidity from infection or cancer. Standard therapeutic approaches are associated with severe adverse events, such cataracts, osteoporosis, infection, diabetes, hypertension and accelerated cardiovascular disease. HELICAL will depart from the current state of the art and foster a precision-medicine approach to vasculitis by developing tools that can identify and predict disease flares, inform clinicians about opportunities to discontinue immunosuppressive medication, and identify therapeutic strategies that target relevant components of the immune system and blood vessel walls, leaving intact the immune system’s ability to fight infection and malignancy.

Data challenge

The successful candidate will develop machine learning and artificial intelligence methods to analyze data from autoimmune vasculitis patients. A computational challenge in the analysis of rare diseases is the high heterogeneity of data sources, where datasets are generated by different studies and techniques, have different data structures and, frequently, are missing data. In addition, there is a need to develop solutions that can ingest, process in real time and present these data in a readily usable format. The student will explore data fusion methodologies in the “small n, big p” domain, and develop prototype machine learning solutions to predict vasculitis flares using diverse multi-dimensional environmental, clinical and app-based data, as well as molecular data from patients.

Requirements

  • Strong background in Physics, Mathematics, Computer Science or similar.
  • Strong background in artificial intelligence, machine learning and/or deep learning.
  • Working knowledge of statistics and mathematical modeling.
  • Working knowledge of Python, C or C++.

In addition, experience in systems biology or systems medicine would be helpful, but not essential.

Diversity

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


Research Staff Member
IBM Research – Zurich

PhD student position: Irregular graph algorithms on accelerator clouds

Ref. 2018-38

About the position

We are seeking an outstanding PhD student to pursue a challenging research project in the field of computer system design for big data analytics and artificial intelligence. The position has a duration of four years. The PhD student will work in the Cloud Storage and Analytics group at IBM Research – Zurich.

Project

Many search and combinatorial optimization problems involve exploration of a large solution space to identify possible solutions to optimize an objective function under given constraints. For instance, in the text and graph-mining fields, finding patterns that exhibit certain properties is typically of high interest. In the case of computer games, such as Go, the search involves finding a set of valid moves that can lead to an advantage and eventual victory. When formulated recursively, such search programs can be very concise. However, the resulting computation is typically very irregular and exhibits limited single-thread performance and SIMD (single-instruction multiple-data) parallelism. One of the objectives of this project is to develop the necessary software and hardware infrastructure to enable scalable implementations of recursive search and optimization algorithms on massively parallel compute clouds.

In the course of this project, we are planning to target massive-scale graph analytics problems, e.g., the Graph Challenge recently created by DARPA and MIT, which involves detecting communities in social networks with billions to trillions of nodes and edges using subgraph-isomorphism and hierarchical-stream-clustering techniques. Such large data sets inherently do not fit into a single storage or memory device and require efficient mechanisms for retrieving information from a distributed storage, e.g., by means of an index. In addition, forming clusters within this data requires the availability of similarity information. Therefore, a secondary objective of this project is to develop efficient information-retrieval mechanisms based on scalable similarity search and indexing techniques.

Requirements

Candidates are expected to have the following background and interests

  • M.Sc. degree in Computer Engineering, Electrical Engineering, or Computer Science
  • A strong background in parallel computer architectures and parallel programming
  • A strong understanding of graph algorithms or machine-learning techniques
  • Excellent software skills and familiarity with functional programming
  • Strong communication skills (both written and verbal)
  • Motivation to acquire new skills and ability to think out-of-the-box

Would be a plus

  • Experience in programming FPGAs, GPUs, and/or many-core processors
  • Experience in hardware description languages and event-driven simulation
  • Familiarity with cloud computing, virtual machines, and containers

Diversity

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

Please send your application documents including CV, publication list, and a brief cover letter explaining your motivation in a single PDF file. Reference letters are welcome. The position is available immediately.


Research Staff Member
IBM Research – Zurich

Post-doctoral researchers: Systems for large-scale machine learning

Ref. 2018-37

About the position

The Cloud Storage and Analytics team at IBM Research – Zurich is conducting state-of-the-art research related to systems for large-scale machine learning. Our work includes design, optimization, and implementation of systems and frameworks for high-performance machine learning in scale-out and cloud environments. The group is working at the intersection of cloud systems and machine learning research, with expertise on fast storage, network, and distributed systems as well as on algorithm design for machine learning. The team has a track record of direct impact on the IBM public Cloud, including a data-storage service that is optimized for nonvolatile storage, as well as a service that accelerates popular ML models on modern CPU/GPU computing systems

We are seeking outstanding post-doctoral researchers to contribute to the above research topics.

Requirements

Candidates are expected to have the following background and interests

  • PhD in Computer Science, Applied Mathematics or a related field
  • Excellent programming skills (C++, Python, C)
  • Strong distributed systems and operating systems background
  • Practical experience with machine-learning frameworks
  • Experience with cloud environments, continuous integration frameworks, and adherence to coding standards
  • Proven track record of conducting independent research
  • Self-motivated and passionate about problem-solving
  • Excellent written and oral communication and teamwork skills

Positions are available immediately for a duration of 18 months. The successful candidates will enjoy an internationally competitive salary and work in a collaborative and creative group in an exclusive research environment.

Diversity

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

Candidates with the background and interests listed above are encouraged to send their CV including publication list and references to:


HR Partner
IBM Research – Zurich
Säumerstrasse 4
8803 Rüschlikon
Switzerland

PhD student positions: Systems for large-scale machine learning

Ref. 2018-35

About the position

The Cloud Storage and Analytics team at IBM Research – Zurich is conducting state-of-the-art research related to systems for large-scale machine learning. Our work includes design, optimization, and implementation of systems and frameworks for high-performance machine learning in scale-out and cloud environments. The group is working at the intersection of cloud systems and machine learning research, with expertise on fast storage, network, and distributed systems as well as on algorithm design for machine learning. The team has a track record of direct impact on the IBM public Cloud, including a data-storage service that is optimized for nonvolatile storage, as well as a service that accelerates popular ML models on modern CPU/GPU computing systems

We are seeking outstanding students to contribute to the above research topics. The students will be conducting work towards a PhD thesis while working at IBM Research. Students will need to enroll at an accredited university and have an academic advisor at the institute.

Requirements

Candidates are expected to have the following background and interests

  • MSc in Computer Science, Applied Mathematics or a related field
  • Excellent programming skills (C++, Python, C)
  • Strong distributed systems and operating systems background
  • Practical experience with machine-learning frameworks
  • Experience with cloud environments, continuous integration frameworks, and adherence to coding standards
  • Proven track record of conducting independent research
  • Self-motivated and passionate about problem-solving
  • Excellent written and oral communication and teamwork skills

Positions are available immediately. The successful candidates will enjoy an internationally competitive salary and work in a collaborative and creative group in an exclusive research environment.

Diversity

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

Candidates with the background and interests listed above are encouraged to send their CV including publication list and references to:


HR Partner
IBM Research – Zurich
Säumerstrasse 4
8803 Rüschlikon
Switzerland

Research Staff Member / Post-doctoral researcher: Cryptography

Ref. 2018-32

About the position

We are seeking to fill several Research Staff Member (RSM) and post-doctoral researcher positions at IBM Research – Zurich in the area of cryptography and privacy.

Particular topics of interest include, but are not limited to

  • Verifiable computing and zero-knowledge proofs
  • Foundations & solutions for real-world cryptography
  • Privacy-enhancing technologies

The cryptography and privacy group at IBM Research – Zurich offers an exciting research environment with the ability to cooperate with researchers working on various aspects of security and cryptography, including lattice-based cryptography, provably secure protocol design, blockchain, and system security.

Cooperation with other academic and industry researchers within IBM as well as acquisition of external research funding, e.g., European grants (including the ERC) is also possible and encouraged.

The positions offer the opportunity to live in the Zurich area, which is consistently ranked as one of the top five cities with the best quality of life.

Requirements

Candidates for both types of openings are required to have a PhD in Computer Science, Mathematics, or related area by the time of appointment and an outstanding research record, demonstrated in the form of publications at top cryptography or security conferences (Crypto, Eurocrypt, CCS, S&P etc.).

The ideal applicant for an RSM position is someone with a demonstrated ability to perform top-notch independent work, and who is also keen on pursuing joint research directions with the current members of the group. The possibility of establishing one’s own research team, including PhD students and post-docs, would also be supported.

Diversity

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

For informal enquiries, please contact or .

To apply, please send your CV, including contact information for three references, to . Review of applications will begin in mid-September and continue until the positions are filled. Ideally, the successful applicants would start at the beginning of 2019, but other arrangements can be negotiated.

Post-doctoral researcher: Magnetic tape storage systems

Ref. 2018-30

About the position

We are seeking an outstanding post-doctoral researcher for research in state-of-the-art magnetic tape storage systems. Magnetic tape storage is rapidly becoming the de facto standard technology for archiving cold data at hyperscale cloud companies and continues to be used extensively in data centers for backup and archiving. Tape’s success is driven by its cost effectiveness and its potential for continued capacity scaling to accommodate the ongoing exponential growth in data. Our research aims at developing the technologies that will enable the continued scaling of IBM’s tape storage products to meet these growing data storage demands.

Tape storage

Requirements

Applicants are expected to hold a PhD in Engineering, Physics or Materials Science and have excellent skills working hands-on in the lab. Familiarity in one or more of the following areas will be useful: magnetic recording, signal processing, electronics, mechatronics, tribology as well as knowledge of VHDL, C and/or DSP programming languages. The candidate will work as part of an interdisciplinary team and should have strong written and oral communication skills. Candidates must have a good track record of research, creativity and ability to meet deadlines. This position is available starting in November 2018 for a duration of 18 months. The successful candidate will enjoy an internationally competitive salary and work in a collaborative and creative group in an exclusive research environment.

Diversity

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

If the above position fits your background and if you are interested in this challenging position, please send your complete curriculum vitae, including a list of publications to:


HR Partner
IBM Research – Zurich
Säumerstrasse 4
8803 Rüschlikon
Switzerland

Post-doctoral researcher: Quantum computing

Ref. 2018-29

About the position

IBM Research – Zurich is seeking a candidate to work as a post-doctoral researcher on experimental quantum computing and simulation with superconducting quantum circuits in the Quantum Technologies group. The focus of the work will be on the development of technologies for scaling superconducting qubit quantum computing architectures towards practical systems. We are looking for a person eager to design, fabricate and test circuits for scalable integrated qubit chips or to develop advanced qubit control and calibration methods. The work will be carried out as part of the IBM Q quantum program and European Quantum Technology projects. The successful candidate will work within a growing international research team in close collaboration with leading players in the quantum computing community.

Requirements

Candidates applying for this position are expected to hold a PhD degree in physics or engineering with a solid background in quantum information processing with superconducting circuits. Applicants at an earlier career stage with a proven skill set relevant to the project may be considered as well. She/he should have either proven experience in performing experiments with superconducting qubit devices including skills in control and measurement automation or expertise in micro- and nanofabrication technologies for scalable systems operating at microwave frequencies and cryogenic temperatures. Ideally, this is paired with expertise in the design and simulation of superconducting microwave circuit.

In addition, the following skills are highly desired:

  • Expertise in microwave engineering and the use of microwave simulation tools such as Ansys HFSS.
  • Experience in cryogenics and the operation of dilution refrigerators.
  • Proficiency in coding (preferably in Python).
  • Ability to conduct independent work and assume responsibility as part of a larger team.
  • Capability and eagerness to learn independently about new subject area(s) and underlying technologies.
  • Strong communication and writing skills.

Diversity

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

Please send your application documents including your CV, a publication list, relevant transcripts and a brief cover letter explaining your motivation in a single PDF file. Please also provide for a reference letter sent directly to the email stated above as well as the name of two further references. This position is available immediately. Applications will be taken into further consideration until the position is filled. Candidates are invited to send their application documents to


Technical Leader Quantum Computing
IBM Research – Zurich

Post-doctoral researcher: CMOS circuits

Ref. 2018-28

About the position

Custom-designed CMOS circuits and dedicated hardware solutions will be required in order to fully exploit the performance of novel computing and communications systems. Scientists at the IBM Research – Zurich Lab are working on several aspects in the fields of computing infrastructure and CMOS technology.

We are expanding our team working on analog and high-speed mixed signal circuits, which is designing and testing power-optimized 7-nm and 14-nm CMOS circuits and is engaged in the development of future device technologies. In the high-speed I/O group, there is an opening for a post-doctoral researcher whose main responsibility is to investigate, design and demonstrate novel CMOS circuits.

Tasks to be performed include

  • Innovative circuit and system solutions for advanced analog-to-digital and digital-to-analog converters, digital signal synthesis and analysis, and protocol processing, using state-of-the-art simulation tools,
  • Circuit characterization and measurement in the laboratory,
  • CMOS device measurements and modelling  at low temperatures,
  • Embedding the dedicated circuits into research systems to demonstrate their functionalities.

Requirements

Candidates are expected to have the following background and interests:

  • CMOS analog/mixed-mode circuit design,
  • Experience with EDA tools such as Cadence, Synopsys and Mentor,
  • Experience with analog and RF measurements,
  • Preferably some experience in CMOS device characterization  and modelling,
  • Preferably some experience in microwave signal processing,
  • Basic programming skills (C, Python, etc.).

Diversity

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

Candidates with the background and interests listed above are encouraged to send their CV including publication list and references to:


HR Partner
IBM Research – Zurich
Säumerstrasse 4
8803 Rüschlikon
Switzerland

Post-doctoral researcher: Quantum optimization

Ref. 2018-27

About the position

A post-doctoral researcher position is available at IBM Research – Zurich in the Quantum Technologies group. Quantum computers have the potential to solve certain problems more efficiently than classical computers. In recent years, research on quantum computing hardware has made significant progress, and first devices are now accessible to the public through the cloud. Therefore, studying applications of quantum computers is becoming increasingly important to leverage their full potential once more powerful machines are available. In that respect, it is crucial to understand the timeline to quantum advantage and business impact. Our group is developing and analyzing new quantum algorithms for a wide range of applications, such as optimization and machine-learning algorithms for finance or supply-chain management.

Project

The focus of this project is on the development and analysis of new quantum algorithms for optimization and machine learning. Additionally, an emphasis will be on finding possible applications relevant in practice, for instance in the financial service sector, such as risk analysis or portfolio optimization. The goal is not only to develop the algorithms, but also implement and test them both via simulation and on real quantum hardware.

Starting date

The position will open immediately for a duration of two years and with the possibility of an extension.

Requirements

The position requires a PhD in Mathematics, Physics or related fields. The candidate must have profound knowledge of optimization, machine learning and quantum computing, as well as broad expertise in coding (preferably in Python) and strong communication and writing skills.

Diversity

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

Candidates are invited to send their application including a CV and corresponding reference letters to:


Technical Leader – Quantum Optimization
IBM Research – Zurich

Post-doctoral researcher: Computer vision

Ref. 2018-26

About the position

Our Computer Vision for AI team is working on cutting-edge research and applications that have a strong impact on the business of IBM and its clients. Focal areas span spatial scene understanding in the context of augmented reality and robotics applications and figure and diagram understanding in the context of document analysis. Our philosophy is to combine classic model-based techniques, for which a strong theoretical foundation exists, with highly experimental deep-learning approaches.

Qualifications

  • PhD in Computer Science, Computer Vision, Robotics or a related field
  • Strong programming skills in C/C++ and Python
  • Strong theoretical understanding of classical computer vision techniques and deep-learning architectures
  • Proven track record of conducting independent research
  • Practical experience with deep-learning frameworks
  • Excellent communication and teamwork skills
  • Experience with continuous integration frameworks and adherence to coding standards.

Diversity

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

Please send your complete CV, including a list of publications and skills, as well as contact information for three references to


IBM Research – Zurich
Säumerstrasse 4
8803 Rüschlikon
Switzerland

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.
Diversity

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.

Contact

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

References

[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.


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Innovating at IBM

At IBM, you have the op­por­tun­ity to work on real prob­lems. In the past few weeks I've spo­ken with cli­ents in ener­gy, auto­motive, health­care, chem­i­cals and the mater­ials sci­ences. The poten­tial for world-chang­ing im­pact is in­cred­ib­ly high.
In addition, whenever an IBMer has a good idea, he or she can be sure the com­pany will in­vest in it and put all re­sources necessary towards making it real.

  • Interview with IBM's Cristiano MalossiCristiano Malossi
    IBM research scientist

Read more about what motivates Cristiano


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