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This position is available for 18 months with the possibility of an extension. The successful candidate will enjoy an internationally competitive salary and work in a collaborative and creative group in an exclusive research environment.

Experience in programming with Python

Have a strong background in computer vision and image processing.

IBM is committed todiversityat 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.

Computing systems for high-performance artificial intelligence (AI) workloads

Studying impact of thermal effects on device performance

The candidate will have the primary responsibility to advance new analytical models for predicting the reliability of Power systems, DRAM modules and flash devices that will be applied in the wild. In addition, the candidate is expected to handle the data selection, cleaning and integration tasks prior to the modeling stage.

Applications should be sent by email, preferably before 1 June 2018.

The main focus will be to provide solutions to the challenges of interpretation, analysis, information extraction and search (both semantic and keyword-based) over large amounts of unstructured text documents, as well as connecting structured and unstructured data. Therefore, knowledge of state-of-the-art NLP and text mining methods, as well as the ability, intelligence and creativity to modify and advance beyond them is very important. Furthermore, experience with applying techniques for information extraction and harvesting knowledge from high-quality Web sources in order to build and curate knowledge bases automatically is highly relevant. Familiarity with deep-learning methods and machine learning is a plus.

Applicants to our team should have a passion for both developing new algorithms and implementing solutions to apply our results to exciting new applications. We work in small, solution-focused teams. It is essential that our team members take initiative in helping us find innovative solutions to problems.

Preferred: Familiarity with big data technologies such as Spark and Kafka.

Within the EC-funded Marie Skodowska-Curie Innovate Training Network Quantum-enhanced Sensing via Quantum Control (QUSCO) we are looking for a talented, skilled and highly motivated candidate interested in implementing quantum computing in superconducting quantum devices. The position entails the development of optimal control methods for superconducting qubits to improve gate fidelities, to optimize system identification and calibration sequences and to investigate the use of optimal control in applications for quantum chemistry and classical optimization problems.

The focus of the project is to investigate new strategies to solve electronic structure problems using quantum algorithms for near-term quantum computing.

More details about the position are available upon request. Contact Dr. Tavernelli.Research Staff Member: NLP and text mining

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.

be pursuing a Masters degree in Engineering or Electrical Engineering, Physics, Nanoscience or related field at a Swiss or other European University,

Interested candidates please send an application including CV, cover letter and academic transcript to

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:

A strong background in machine learning with a specialization in time and event series analysis, deep learning and potentially survival models,

Be familiar with deep learning principles and frameworks.

Modeling and simulation of physical phenomena governing thermal effects such as self-heating

In theNeuromorphic Devices and Systemsgroup, an opening is available for a post-doctoral researcher. The main responsibility is to establish and characterize novel photonic neural network technologies and devices. The integration of thin IIIV layers on silicon photonics for optical gain to enhance the functionality of neuromorphic systems is the main focus of this position.

The successful candidate will conduct research in the IBM Research Zurich Laboratory involving one or several of the following topics

A PhD research position is available at the IBM Research Zurich Laboratory as a part of the H2020COSMICconsortium focused on understanding disorders of the adaptive immune system.

Evaluation of newly developed hardware networks with common cognitive benchmarks and analysis of their applicability to real-world problems.

Embedding the dedicated hardware devices into a neural network systems to demonstrate its functionalities

Field programmable gate arrays for the cloud

Knowledge of reliability of IT components (in particular volatile / non-volatile memory) from a systems perspective is a strong plus,

Proficient in Python. Knowledge of other programming languages desired, but not necessary.

Have strong technical skills (experience in C/C++).

Bachelors degree in Computer Science or related field

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:

If youre interested, please send a short e-mail with your CV, a copy of your most recent grades, and information on your availability toDr. Diego Ortiz.

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.

The ideal candidate is expected to hold a PhD in Computer Science, preferably with an emphasis on machine learning or statistics,

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

A strategic focus area for the Foundations of Cognitive Solutions team at IBM Research Zurich is to develop cognitive technology and solutions in the healthcare domain. By exploiting the large amount of existing public and clinic-specific medical data, we are creating systems that can improve patient care by assisting medical professionals. Our work environment is exciting, challenging, and unique since it combines fundamental research and solution engineering focusing on industry projects, which ensures that we develop innovative solutions that are valuable for real-world applications.

Candidates must hold a Masters degree in physics, ideally with a solid background in quantum mechanics and quantum information processing with a focus on superconducting circuits. Specific interest and know-how in instrumentation and software control as well as numerical computation methods is a prerequisite. Good knowledge of Python and C++ is desired. Candidates must be curious to learn or expand their expertise on microwave engineering, signal processing, low-temperature physics, control and measurement automation, data analysis and coding. Owing to EC regulations, the successful candidates must not have been resident of the host country for more than 12 months in the past three years.

Information content of both scientific and professional documents (e.g. papers, reports, patents, financial or medical reports) is often communicated in the form of diagrams. The goal of these diagrams is to visualize data that explain, describe or emphasize the textual content of those documents. When documents are rasterized and stored as bitmaps (e.g. through scanning or faxing), the structure and semantics of the content are no longer machine-readable.

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:

Candidates applying for this internship should fulfill the following requirements:

Candidates should have a PhD in Computer Science, NLP, machine learning, computational linguistics or equivalent with a track record in NLP, text mining, and/or machine learning. We expect strong analytical and problem-solving skills, strong programming skills in Java/Python or similar, the ability to conduct independent research, as well as excellent communication and team skills. Software engineering experience, familiarity with R and Big Data analytics is a plus.

We are seeking to fill a Research Staff Member position available immediately at IBM Research Zurich in the area of NLP and text mining.

Background:EU countries face large health challenges to combat chronic diseases. Recently, systems medicine has emerged as a promising discipline to accelerate the translation of basic research into applications for improved diagnostics and personalized treatment. Its power arises from the integration of laboratory and computational approaches across several research disciplines and sectors to solve clinical problems.

For further information, please visit our.

New computing paradigms bring the promise to extend the functionality of todays 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.

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

At IBM Research Zurich, we employ image processing, pattern recognition, machine learning and NLP technologies to develop technologies for diagram understanding with scientific contributions in the area of automatically extracting relationships from interaction networks.

This post-doctoral researcher position has a duration of 24 months.

Developing an experimental setup to execute software-controlled training and interference tasks on the photonic hardware circuits.

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.

I/O link technology / next-generation fast link transmission

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:

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 lifes work than any humans before us. This is our vision for the future.

OurCloud & Computing Infrastructuredepartment has open internships / semester and Masters thesis / PhD positions. Some of our key projects are:

Keywords: Mechanistic models of cancer, systems modelling, statistical inference.

Strong background in Physics, Mathematics, Computer Science or similar.

For more information please contact Dr. Bert Offrein at the address indicated below. Applications should be sent by email toDr. Bert Jan Offrein, preferably before 1Apr2018.

Optimized infrastructure for analytics including Spark/ML

Working knowledge of Matlab, R or equivalent.

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.

Familiarity with chemoinformatics and developing predictive models using molecular descriptors of compounds is desired but not essential

be highly motivated, creative and able to work independently.

In theNeuromorphic Devices and Systemsgroup, 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.

A post-doctoral position is available immediately in theSmart System Integrationgroup at IBM Research Zurich in the field of research and development of applied augmented intelligence. The research will take place within an inter-disciplinary team involving development and improving wearable sensing technology and analyzing the resulting data using cognitive algorithms including cutting-edge Watson APIs. This effort will contribute to IBMs position as global leader in the development of radically innovative big data and augmented intelligence solutions.

Familiarity with deep-learning frameworks (e.g., TensorFlow) would be highly beneficial,

(b) Schematic illustration of said structure.

Within the EC-funded Marie Skodowska-Curie Innovate Training Network Quantum-enhanced Sensing via Quantum Control (QUSCO) we are looking for two talented, skilled and highly motivated candidates interested in quantum information science with superconducting quantum devices. The position entails the development of optimal control methods for superconducting qubits to improve gate fidelities, to optimize system identification and calibration sequences and to investigate the use of optimal control in applications for quantum chemistry and classical optimization problems. The project ties in directly with the IBMs efforts to operate a practicalquantum computerand make it accessible.

Hands-on experience with large-scale data processing techniques

We are seeking an outstanding post-doctoral researcher for state-of-the-art predictive analytics applied to IT components, in particular Power systems and flash. Our research aims at identifying degradation indicators from rich historical event logs and telemetry data, and using those to accurately predict future failures and performance degradation events in the field.

Dr. Mara Rodrguez Martnez

preferably have a background in solid-state physics or devices,

The candidate must be self-driven, highly motivated and is required to multitask efficiently.

Dr. Ali Oskooei.Masters thesis: Thermal effects in electronic devices

Modeling of exascale computing systems

Characterization of electrical and optical building blocks

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.

Excellent coding skills in R, Python, and potentially Scala,

The position will open immediately for an initial duration of three years.

Developing computational tools with the ability to ingest rasterized documents, to automatically extract all their visual and textual content, to interpret and semantically represent it for large collections of documents can greatly accelerate data-driven cognitive analysis.

have excellent English communication skills,

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

Important tasks to be performed are:

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

IBM is committed todiversityat 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.

Executing small-scale cognitive algorithms on the newly developed systems for benchmarking.

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.

Manager Neuromorphic Devices and Systems

Approach:COSMIC will focus on B-cell neoplasia and rheumatoid arthritis, prototypical diseases originating from abnormal functioning of immune cells. Among other approaches, the research will be focused on the development of mathematical models of the germinal centers, specialized compartments of the immune systems where B cells proliferate and differentiate into memory B cells and plasma cells. The candidate will continue ongoing work at IBM and further develop stochastic models of the germinal center that aim to elucidate the mechanisms underlying healthy and abnormal B cell differentiation. The model will be fitted to experimental data produced within the consortium using state-of-the-art optimization techniques.

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

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

Design of next-generation integrated photonic recurrent neural networks, interfacing with collaborators in the field of mathematics.

RF (S-parameter) and DC measurements of field-effect transistors

New computing paradigms promise to extend the functionality of todays von Neumann-based systems. Artificial intelligence and neural network-based systems have proved to be good choices to classify 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, building on existing integrated electrical and optical platforms. This work is embedded in several EU Horizon2020 projects.

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

Candidates are expected to have the following background and interests:

Hardware security modules to protect the most valuable encryption keys

A strong quantitative background and hands-on experience with machine learning and computational methods

Please send a cover letter with a summary of research interests and a CV to

This project offers the unique opportunity to interface directly between experiment and theory: The PhD student will be working first at the Saarland University on theoretical optimal control and system identification before bringing in the acquired theory expertise to IBM Research Zurich in the second part of the PhD research. During both periods, the student will be supervised by Prof. Frank WilhelmMauch at the Saarland University and will have the opportunity to obtain a degree there. The project ties in directly with IBMs efforts to operate and make accessible a practical quantum computer.

To apply for the position please send your CV, a statement of research interests with a short description of your background, motivation and skills (max. 2 pages) and two reference letters directly sent toStefan Filipp and Frank Wilhelm-Mauch. Consideration of applications will begin immediately and will continue until both positions are filled.

An excellent publication track record in top conferences and journals,

Design of electrical and optical devices for neural networks

Characterization and benchmarking of the recurrent neural networks fabricated in IBM cleanroom facilities.

The candidate must hold a Masters degree in Physics, ideally with a solid background in quantum mechanics and quantum information processing with a focus on superconducting circuits. He/she should be curious to learn more about mathematical control theory and advanced data analysis methods such as Bayesian inference or machine learning. Good knowledge of at least one of Python, Matlab, and C++ is desired. The candidate should be open to hands-on experimentation and understand instrumentation and its software interface. Owing to EC regulations, the successful candidate must not have been a resident of Germany or Switzerland for more than 12 months in the past three years.

The position requires a Masters degree in Computation, Theoretical Chemistry, Physics or Quantum Information Theory. The candidate must have a good knowledge of the fundamentals of quantum mechanics and coding expertise in Python and C++. Competence in quantum chemistry (post-HF methods and/or quantum Monte Carlo) are also required.

The ideal candidate for this project should

In addition, experience in systems biology or systems medicine as well as machine learning would be helpful, but is not essential.

Completed Bachelors degree in Computer Science, Software Engineering, Software Architecture, or equivalent.

The successful candidate will have a strong interdisciplinary background in computer or informatics engineering, and experience in developing internet of things or wearable devices as well as pattern recognition and deep learning. The highly motivated individual will join our multi-disciplinary research team to advance our effort in the internet of the body project in theIBM Research Frontiers Institutewith the goal to provide people with a healthier way of living and to augment their senses. The position will focus on experimental data gathering and software development for embedded wearable systems and edge computers. The objective is to apply advanced cognitive algorithms to the acquired data and contribute to develop the field of machine intellig

Familiarity with big-data processing frameworks (e.g., Spark stack) would be highly beneficial,

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.

Relating thermal effects to 3D sequential stacking of device layers.

At IBM Research Zurich, we are developing cognitive solutions for challenging NLP and text mining problems on very large, domain-specific, unstructured text documents comprising a mixture of both human and machine generated content. The successful candidate will be a part of a dedicated, international team that aims to provide efficient solutions to these problems.

Working knowledge of statistics and mathematical modeling.

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

We are interested in investigating these heterogeneities using machine learning and computational methods. The successful candidate will develop predictive models using a combination of molecular descriptors of drug compounds as well as available drug screening datasets such as the Sanger institutes Genomics of Drug Sensitivity in Cancer (GDSC) database.

We are looking for highly motivated and enthusiastic students in Computer Science or a related discipline who would be interested in improving their practical skills working with an experienced team at IBM Research in Rschlikon. Preferred duration is 6 months, but we can discuss alternatives (4 to 12 months).

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.

Manager Neuromorphic Devices and Systems

This project offers the unique possibility to interface directly between experiment and theory: One PhD student will be located at the IBM Research Zurich laboratory assisting the experimental team, the second PhD student will work first at the Saarland University on theoretical aspects before bringing in the acquired theory expertise to IBM Research Zurich in the second part of the PhD. Both PhD students will be supervised by Prof.Frank Wilhelm-Mauch at the Saarland University and able to obtain a degree there.

Predicting the response of a cancerous tumor to therapy is an important objective in cancer research. A major area of interest is to identify genomic biomarkers in tumors that can help predict their response to a certain cancer drug. It has been shown that there is heterogeneity in drug sensitivity biomarkers, even for drugs that belong to the same class, such as EGFR inhibitors. There is also heterogeneity in the efficacy of various drug compounds within the same class.

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

To apply for the position please send your CV, a statement of research interests with a short description of your background, motivation and skills (max. 2 pages) and two reference letters directly sent toFrank WilhelmMauch and Stefan Filipp. Consideration of applications will begin immediately and will continue until the position is filled.

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