Master’s thesis: Thermal effects in ultrascaled Al/Ge nanowires

Ref. 2018-36

About the position

Considering that thermal design constraints are one of the most challenging problems for the microelectronics industry today, it comes as a surprise that so little is known about heat generation and dissipation on the nanoscale. In fact, there is no established method to perform temperature measurements at a spatial resolution that matches typical feature sizes found in today’s cutting-edge integrated circuits. To tackle these challenges, our team is developing new methods and tools for measuring temperature and heat transport down to the atomic scale. Our setups operate in IBM’s unique noisefree labs, which are among the best shielded nanotechnology labs in the world. Our work is relevant to developing next-generation computers and scientific models. We are helping to identify future technologies by evaluating new materials and device concepts from a thermal perspective.

You will join our nanoelectronics team and learn how to use a custom-built scanning thermal microscope, which has recently demonstrated world-record performance in terms of spatial resolution and sensitivity. You will help to further improve the machine and perform your own experiments. This is an opportunity to work in a state-of-the-art exploratory research facility. You will have close interaction with leading experts in the fields of nanofabrication, device physics and high-sensitivity transport measurements. You will become familiar with our specialized laboratory and cleanroom facility. You will work in a collaborative and creative group in a lively research environment.

The topic of your thesis will be the investigation of thermal effects in single crystalline Al/Ge nanowires with very small diameters. Pure Al nanowires have shown the capacity to carry extremely high electrical current densities, meeting the targets for interconnects in future technology nodes. It has also been shown that a Ge section incorporated in such a wire exhibits quantum ballistic transport at room temperature and photon detection at the theoretical limit of sensitivity. Devices based on this material system could be applied to quantum computing and high-resolution light detection and imaging. Your role is to study how thermal energy is dissipated and transported by electrons and phonons in these quasi one-dimensional nanoelectronic systems, and to analyze and interpret the findings together with the IBM Research staff and our partners at Vienna University of Technology.

 

topography and temperature signal, measurement setup, chips

A 3D overlay of topography and temperature signal (top), a peek into the custom-made measurement setup you will be working with (left), and some chips of the type you will be investigating (right).

Requirements

We are looking for a highly motivated and adventurous Master’s student with a major in Physics, Electrical Engineering, Mechanical Engineering, Materials Science, or related field. Basic programming experience in Python and Matlab would be helpful.

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 you are interested in this challenging and cutting-edge Master’s project and the above description matches your profile, please do not hesitate to send your CV, together with a transcript of records, to


IBM Research – Zurich
Säumerstrasse 4
8803 Rüschlikon
Switzerland
044 724 8031

Application per email is preferred. Please note that we cannot offer any remuneration to Master’s students. Therefore, this opportunity is mainly targeted at students enrolled at ETH Zurich who are already based in the area.

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

PhD student position: Nanoscale systems

Ref. 2018-34

About the position

A PhD position is available in the Physics of Nanoscale Systems group of the Science & Technology Department at IBM Research – Zurich. Our group studies novel concepts to separate and analyze nanoparticles in liquids. Although nanoparticles are becoming increasingly abundant due to their heavy use in industry, it remains a challenge to detect, manipulate and analyze them. We will contribute novel technology that may be used in the future to assess nanoparticle content quantitatively in solutions.

Inspired by how molecular motors work in biology, we jave developed an artificial Brownian motor to transport and separate nanoscale particles in fluids (Skaug et al., Science, 359, 1505, 2018). We have developed a toolset based on geometry-induced electrostatic trapping and laser scanning interferometric detection that allows us to manipulate and observe nanoparticles in a nanofluidic channel with high temporal and spatial resolution. Using this toolset, we observed and rationalized a reversal in the transport direction of the motors at high frequencies (Schwemmer et al., Phys. Rev. Lett. 121, 104102, 2018).

In this previous work we established models that allow us to extrapolate the behavior of these motors for smaller particle sizes. The models predict that particle separation is feasible with an unprecedented resolution of 1 nm in particle radius. Moreover, the method is expected to work for very small nanoparticles such as DNA molecules and proteins. Being able to manipulate, transport and separate such molecules will pave the way for novel bio-medical applications.

For the current position it is planned to explore the physical limits in terms of particle separation resolution and particle detection sensitivity. The student will design and simulate experiments, fabricate devices, and conduct and characterize the experiments. Simulation tools are in place and he or she will be guided initially by experienced researchers in the field.

Requirements

Candidates applying for this position are expected to hold a Master’s degree in Physics, Physical Chemistry or Nanoscience, ideally with a background in colloidal physics, microfabrication or scanning probe methods. Also desired is some proficiency in programming (preferably in Python), a capability and eagerness to learn independently about a new subject, and strong communication and writing skills.

The successful candidate will acquire profound knowledge in nano-particle interactions in liquids, single-particle detection and tracking, soft-matter physics and related physical chemistry, and atomic force microscopy (AFM). The work is embedded in a research group comprising experts in probe microscopy, nano-fabrication, polymer physics, MEMS fabrication, Si technology, self-assembly and micro-fluidics.

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. Candidates are invited to send their application documents to


Group Leader Nanofabrication
IBM Research – Zurich

PhD student position: Nanoscale thermal transport

Ref. 2018-33

About the position

Nanoscale thermal transportWe are looking for a highly motivated PhD student for our activities in nanoscale thermal transport. We aim to advance the understanding of heat generation and dissipation in nanoscale devices with the goal of developing technologies for future nanoelectronic devices and their energy challenge. In several projects, activities range from performing experiments of fundamental nature to engineering devices and demonstrators. The PhD project will use thermal imaging techniques to identify current paths in devices designed for neuromorphic computing.

The successful candidate will have access to a laboratory fully equipped for the characterization of nanoelectronic devices at high precision. Our setups operate in IBM’s unique noise-free labs, which are among the best shielded nano­technology labs in the world Furthermore, a fully equipped, state-of-the-art clean room is available for sample fabrication. This position is available for a duration of three years in a collaborative and creative group in a lively research environment.

Requirements

Applicants are expected to hold a Master’s degree in Physics or Engineering with a strong background in nanometer-scale physics. The ideal candidate is very talented, creative, highly motivated, has excellent communications skills and is open to working in an international, multidisciplinary team.

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 you are interested in this challenging position and you fulfill the requirements, please send your complete curriculum vitae and the names of three references by email to

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.

Master’s students at ETH: Applications of spiking neural networks in Big Data

Ref. 2018-31

About the position

Neural networkArtificial neural networks have been the driving force of artificial intelligence in recent years, currently transforming many industries. However, these conventional neural networks still suffer from several severe limitations, most importantly their need for human supervision in their training, the enormous resource consumption that they incur in terms of data and energy, and their lack of flexibility such as multitasking and adaptability to changing conditions. These challenges need to be overcome before industries such as data analytics, the Internet of Things, or autonomous drones can be fully equipped with cognitive computing capabilities. Spiking neural networks are viewed as the next generation of neural networks and are known to provide greater computational power while consuming fewer resources. These algorithms are capable of learning and computing in ways closely resembling our understanding of how the biological brain functions. In addition, spiking neural networks can be very efficiently implemented by exploiting the physical properties of new technologies such as memristive devices.

At IBM Research – Zurich we have been contributing to advances in the field through hardware demonstrations of spiking neural elements mostly with phase-change memory devices. Our recent algorithmic work focuses on the core challenges in exploiting the computational advantages of spiking neural networks. We are also exploring new application domains of spiking neural networks such as cognitive storage for Big Data systems. We are inviting applications from Master’s students at ETH to conduct their thesis project at IBM Research – Zurich on this exciting new topic. A successful project would have significant impact in the field of cognitive computing.

Requirements

The ideal candidate should have a multi-disciplinary background, strong mathematical aptitude and programming skills. Prior knowledge on spiking neural networks is a bonus but not necessary. Please note that this will be an unpaid position for Master’s students from ETH Zurich as per the university regulations.

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 you are interested in this challenging position on an exciting new topic, please send your complete curriculum vitae including a transcript of grades by email to:


Exploratory Memory and Cognitive Technologies
IBM Research – Zurich

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

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 get 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:

  • Bachelor’s degree in Computer Science or related field
  • Hands-on data science on the prevalent platforms, as well as the basic fundamentals of machine learning
  • Bonus: Proficiency in Python and some experience with anomaly-detection techniques
  • Preferred: Familiarity with big-data technologies such as Spark, Kafka and BigSQL.

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:

Student internship: Big data time series analysis using machine learning

Ref. 2018-15

About the internship

Analysis of continuous and discrete valued time series is essential for intelligent management of complex systems in a range of industries. Predictive maintenance aims to prevent system failures by predicting them before they occur, avoiding the consequences of outages and costly repairs.

Machine learning is widely applied for understanding, forecasting and predicting based on time series data. In order to train and evaluate models continuously on near-real-time system data, a robust and scalable data processing infrastructure is required. We apply state-of-the-art technologies to enable efficient analysis of hundreds of millions of records per day. We are looking for an intern with a relevant background to join us in developing a big data infrastructure.

The successful candidate will get the opportunity to participate in an advanced machine learning project that aims for high business impact by avoiding unexpected outages in managed IT systems, and gain valuable experience in processing large quantities of data to create actionable insights.

Requirements

Candidates are expected to have the following background and interests:

  • Bachelor’s degree in Computer Science or related field
  • Hands-on experience with large-scale data processing techniques
  • Good confidence in coding Scala
  • Preferred: Familiarity with big data technologies such as Spark and Kafka.

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

Internships / semester and Master’s thesis / PhD projects: Cloud & Computing Infrastructure department

Ref. 2018-13

The world is at a major turning point: Technology is enabling entirely new forms of business operations, business models, industries and outcomes. We have exponentially more power to reach the full potential of our life’s work than any humans before us. This is our vision for the future.

Want to be part of this journey?

Our Cloud & Computing Infrastructure department has open internships / semester and Master’s thesis / PhD positions. Some of our key projects are:

  • Cloud storage and security
  • System-aware machine learning
  • I/O link technology / next-generation fast link transmission
  • System security
  • Advanced tape technologies
  • Hardware security modules to protect the most valuable encryption keys
  • Field programmable gate arrays for the cloud
  • Optimized infrastructure for analytics including Spark/ML
  • Memory & cognitive technologies
  • Neuromorphic
  • Modeling of exascale computing systems
  • Computing systems for high-performance artificial intelligence (AI) workloads
  • Archival storage
  • Blockchain

For further information, please visit our project webpages.

Your qualifications

You are studying Computer Science, Mathematics or similar Engineering topics and you are very interested in one of the above research fields. We are looking for self-driven and highly motivated candidates.

Diversity

IBM is committed to diversity at the workplace. We offer a diverse, independent professional activity, with experienced colleagues in a friendly atmosphere on our campus. You will find a dynamic, multi-cultural environment, and flexible work conditions.

How to apply

If you are interested, please send your complete CV, copies of diplomas and, if available, letters of reference to:

Master’s thesis: Thermal effects in electronic devices

Ref. 2018-08

Project description

The continuous scaling of transistors in CMOS technology has led to a tremendous increase of device density, with CPU chips typically employing billions of transistors. Simultaneously, power density has increased, leading to unwanted effects from self-heating. To mitigate these effects, a better understanding of the mechanisms of self-heating are needed, in particular in non-standard material systems, such as III-V compound semiconductors.

This project aims to examine self-heating effects in state-of-the art field-effect transistors based on III-V compound semiconductors. The work will entail:

  • RF (S-parameter) and DC measurements of field-effect transistors
  • Modeling and simulation of physical phenomena governing thermal effects such as self-heating
  • Studying impact of thermal effects on device performance
  • Relating thermal effects to 3D sequential stacking of device layers.

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

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

STM of III-V transistor Schematic of III-V transistor

(a) Scanning tunneling electron microscopy image of a III-V transistor integrated on top of Si CMOS logic fabricated at IBM Research – Zurich.
(b) Schematic illustration of said structure.

Requirements

Applicants are expected to Experience with simulation and modeling is a plus

  • be pursuing a Master’s degree in Engineering or Electrical Engineering, Physics, Nanoscience or related field at a Swiss or other European University,
  • preferably have a background in solid-state physics or devices,
  • have excellent English communication skills,
  • be highly motivated, creative and able to work independently.

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
.

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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