Signal Processing Theory and Methods

The Department of Computer Science at the National University of Singapore is seeking a postdoctoral fellow to work with Dr. Jonathan Scarlett.

The postdoctoral fellow will work on problems at the intersection of machine learning, statistical signal processing, information theory, and their intersection, with topics potentially including the following:
- Algorithms and theory for high-dimensional inference and learning (e.g., graph learning, structured estimation)
- Sequential decision-making algorithms under uncertainty (e.g., black-box optimization, bandits, ranking)
- Information-theoretic limits for problems in statistical inference, learning, and optimization
- Machine learning methods applied to communication problems
Further information on Jonathan Scarlett's research interests can be found at https://www.comp.nus.edu.sg/~scarlett/.

The position is expected to last for at least 1 to 2 years. The candidate should have a PhD in a relevant area such as machine learning, statistical signal processing,  information theory, or theoretical computer science, and a strong publication record. 

The salary will be very competitive, and commensurate with the candidate's abilities and track record. 

Applicants should submit a detailed CV and a short statement of research interests to Jonathan at scarlett@comp.nus.edu.sg. Shortlisted applicants will later be asked to arrange for at least two reference letters to be sent to the same address

The Department of Computer Science at the National University of Singapore is seeking a postdoctoral research fellow to work with Dr. Jonathan Scarlett.

The postdoctoral fellow will work on problems at the intersection of information theory, statistical signal processing, and machine learning, with topics potentially including the following:
- Algorithms and theory for high-dimensional inference and learning (e.g., graph learning, structured estimation)
- Sequential decision-making algorithms under uncertainty (e.g., black-box optimization, bandits, ranking)
- Information-theoretic limits for problems in statistical inference, learning, and optimization
- Machine learning methods applied to communication and signal processing problems
Further information on Jonathan Scarlett's research interests can be found at https://www.comp.nus.edu.sg/~scarlett/.

The position is expected to last for at least 1 to 2 years. The candidate should have a PhD in a relevant area such as information theory, statistical signal processing, machine learning, or theoretical computer science, and a strong publication record. 

The salary will be very competitive, and commensurate with the candidate's abilities and track record. 

Applicants should submit a detailed CV and a short statement of research interests to Jonathan at scarlett@comp.nus.edu.sg. Shortlisted applicants will later be asked to arrange for at least two reference letters to be sent to the same address.

The Institution for Future is a newly established department in Qingdao University, nestling under the mountain and beside the sea in the beautiful coastal city of Qingdao. We have millions of funding and now seeking for some teammates who wish to lead the future with us. The following five labs are opening for candidates at all ranks (Post-Docs, assistant, associate, and full professor):

• Lab of Artificial Intelligence
• Lab of Robotics
• Lab of Intelligent Manufacture
• Lab of Unmanned Systems
• Lab of Fundamental Research

We are interested in candidates in broad areas, including but not limited to: control theory and technology, computer science, signal processing, robotics, unmanned systems, artificial intelligence. You will be given large freedom for your own research and/or industrial projects.

The assistant professor position and Post-Doc position is only for young scientists under 35. The Post-Doc position lasts about 2 years (usually no less than 20 months, no more than 3 years). Special offers are available for outstanding candidates now.

To apply or to request more information, please contact jwy1992@126.com as soon as possible. Application documents should include a detailed CV, publication record, your best 2 papers, and preferably a proposal for your future research.

About the position:

We have a vacancy for a PhD Research Fellow position at the Department of Electronic Systems (IES). The PhD position is for up to 4 years with 25% work assignments for NTNU IES.

Job description:

The pervasion of the Internet of Things (IoT), which connects numerous sensors, actuators, appliances, vehicles etc., has a strong impact on the evolution of smarter and greener cities as well as on environmental monitoring. A basic tenet underlying all key functionalities of the IoT is situational awareness, i.e., the ability to capture events and derive accurate critical information for decision making that enable timely action in a heterogeneous and highly dynamic environment. This calls for an intelligent infrastructure that is autonomous, dependable, and resilient to natural or man-made disturbances. A critical component of such an infrastructure comprises myriads of information-gathering sensors deployed at many points of concern in the city. The sensors deployed in smart cities' IoT constitute critical data sources, on which the ensuing analytics and control actions depend. Those sensors are interconnected through the internet, forming an important part of IoT, and most likely powered only by batteries. To ensure that the sensors function effectively, we need to take a holistic approach to designing secure sensor networks with energy-efficient functional algorithms starting with sensing, followed by data processing and communication to ensure reliable decision making to enable timely actions that make possible long lasting secure and dependable functionality.

The PhD projects will be around developing and analyzing new efficient statistical learning algorithms for distributed inference to improve data quality, reliability, privacy and security of the physical-layer signals in IoT. The aim is to go beyond state-of-the-art solutions, embrace a secureby-design philosophy by exploiting additional information available at the physical layer, and take a holistic approach that starts with smart sensors, smart inference, and secure two-way communication among all the devices in the network, and energy-efficiency.

We seek a highly-motivated individual who has

• strong mathematical background and a research-oriented master thesis in a related field, e.g., signal processing, information theory, statistical machine learning, applied mathematics, or optimization
• experience with programming

Publication activities in the aforementioned disciplines will be considered an advantage but is not a requirement.

Qualification requirements:

The qualification requirement is completion of a master’s degree or second degree (equivalent to 120 credits) with a strong academic background in Electrical Engineering, Applied Mathematics, Computer Science, or other relevant disciplines with a grade of B or better in terms of NTNU’s grading scale. Applicants with no letter grades from previous studies must have an equally good academic foundation. Applicants who are unable to meet these criteria may be considered only if they can document that they are particularly suitable candidates for education leading to a PhD degree.

Application:

For more detailed information and application submission, please visit the following link:

https://www.jobbnorge.no/en/available-jobs/job/158760/phd-position-in-signal-processing-for-privacy-preserving-distributed-learning-in-iot

The submission should contain an application letter describing your motivation, relevant experience, skills and qualifications, and a brief research vision for the position (maximum 2 pages) along with a CV, publication list, MSc thesis, letters of reference, proof of fluency in the English language (if applicable) and grade transcripts from both bachelor and master’s degrees.

NATO Vacancy 180543 

Scientist, Tracking and Data Fusion

Primary Location: Italy-La Spezia

NATO Body: Centre for Maritime Research and Experimentation (CMRE)

Schedule: Full-time

Salary (Pay Basis): 5,285.21Euro (EUR) Monthly

Grade A.2

Link: http://www.cmre.nato.int/employment/current-vacancies/doc_download/1211-scientist-tracking-and-data-fusion  

Description

Do you have recent and relevant experience in developing and implementing advanced techniques for Data Fusion and Tracking? Do you have a demonstrated track record of implementing advanced algorithms into software and using this software to process and understand experimental data, leading to the generation of high quality scientific papers and technical reports? Do you have experience interacting with and satisfying external technical customers?

If the answer to the above questions is yes, then this position may be ideal for you.

1      POST CONTEXT

The Centre for Maritime Research and Experimentation (CMRE) is an executive body of the Science and Technology Organization (STO) and is governed by the provisions of the STO Charter. Within the framework of the STO in-house delivery business model, the CMRE organizes and conducts scientific research and technology development and deliver innovative field-tested S&T solutions to address the defence and security needs of the Alliance.

The CMRE Research Department conducts research oriented toward systems and physical processes in the maritime domain.

The Tracking and Data Fusion Scientist is an A2 position in the Maritime Unmanned Systems for ASW (MUS for ASW) project within the CASW programme.  Duties will be performed under the guidance of the MUS for ASW Project Leader and the CASW Programme Manager.

2      MAIN ACCOUNTABILITIES

The candidate will conduct research on the use of autonomous active and passive sonar networks for the tracking of submarine targets. Duties will include: experimentation with manned and autonomous sensor networks during sea trials; development of advanced multi-target tracking and data fusion algorithms; the testing of these algorithms on experimental data collected during sea trials, both in real-time and in post-analysis, to validate and further guide the development of the algorithms; and the writing of technical documents documenting achieved results. 

The incumbent maybe required to perform other related duties.

3       QUALIFICATION AND EXPERIENCE

3.1      ESSENTIAL 

• A University education in engineering, computer science, physics, mathematics or similarly rigorous overlapping discipline.
• A minimum of 1 year postgraduate experience after a Ph.D., or 3 years after a Master’s degree, or 7 years after a Bachelor’s degree.
• Expertise in tracking and data fusion.
• Strong research record as evidenced by peer-reviewed publications and/or technical reports.
• Proven ability to analyse large quantities of experimental data, to determine findings from the analysis, and to report on them.
• Proven ability to develop tracking and data fusion algorithms into MATLAB, Python or other scientific programming languages that provide demonstrable improvements to the achieved performance of tracking algorithms working on experimental data.
• Most of the work of the CMRE is conducted in the English language, and therefore an advance knowledge of English, both written and spoken, is essential.

3.2      DESIRABLE QUALIFICATIONS

• Expertise in active or passive sonar for Anti-Submarine Warfare or other underwater detection applications.
• Expertise developing real-time signal processing, tracking and data fusion solutions.
• Implementing algorithms onto embedded systems .
• Expertise in multi-target tracking.
• Expertise in machine learning.
• Experience leading scientific project teams.
• Demonstrated track record delivering high quality and valued products, such as reports or algorithms, to a customer.
• Experience working in multi-disciplinary environments with experts from other domains.
• International reputation.
• Membership in and service to professional societies.
• Experience interacting with high-level civilian and/or military decision makers.

4       COMPETENCIES

 Competencies required:

• Working with People: Shows respect for the views and contributions of other team members; shows empathy; listens, supports and cares for others; consults others and shares information and expertise with them; builds team spirit and shows flexibility in reconciling conflicts; adapts to the team and fits in well.
• Coping with Pressures and Setbacks: Maintains a positive outlook at work; works productively in a pressurised environment; keeps emotions under control during difficult situations; handles criticism well and learns from it; balances the demands of a work and personal life.
• Applying Expertise and Technology: Applies specialist and detailed technical expertise; uses technology to achieve work objectives; develops job knowledge and expertise (theoretical and practical) through continual professional development; demonstrates an understanding of different organisational departments and functions.
• Adapting and Responding to Change: Adapts to changing circumstances; tolerates ambiguity; accepts new ideas and change initiatives; adapts interpersonal style to suit different people or situations; shows an interest in new experiences.

Development of new optical transmission methods based on nonlinear Fourier transform.

Applications are invited for a three year prestigious Postgraduate studentship (leading to a PhD) as MSCA Early Stage Researcher, supported the School of Engineering and Applied Science through MSCA ITN European Industrial Doctorates project FONTE, to be undertaken within the Aston Institute of Photonic Technologies (AIPT) [http://www.aston.ac.uk/eas/research/groups/photonics/] at Aston University (Birmingham; UK).

The successful applicant will join an established experimental group working on the applications of the nonlinear Fourier transform signal processing method for the fibre nonlinearity mitigation and the development of the new generation of extra-high-capacity optical networks and related concepts. Secondments: The studentship is offered in collaboration with world-leading industrial unit: Nokia Bell Labs (NBL), Stuttgart, Germany (no less than 18 months at NBL). The project research time and trainings will be equally split between AIPT and NBL. Close collaboration and visits to other three FONTE partners, Technical University of Denmark, Telecom ParisTech (France), and Technical University of Delft (the Netherlands), will be carried out along the project. The position is available to start in September/October 2018 (subject to negotiation)

Salary
The successful candidates will be employed on a full-time basis with a competitive salary in accordance with the Marie Sklodowska-Curie Actions regulations for Early Stage Researchers (ESRs) and the personal circumstances of the applicant. The successful candidate will receive a financial package consisting of MSCA living allowance and mobility allowance, together £32,750 pa. Eligible candidates will also receive an additional family allowance according to the rules of the MSCA.

PhD studentship bursary
This studentship includes a fee bursary to cover the home/EU fees. Applicants from outside the EU may apply for this studentship but will need to pay the difference between the ‘Home/EU’ and the ‘Overseas’ tuition fees, the difference currently being £12,005 pa in 2017/18. Confirmation that this funding support is in place for the full duration of the PhD studentship will be required as part of the application process

Background of the Project
Nonlinear transmission effects in optical fibre are now a major limiting factor in modern fibre-optic communication systems. Nonlinear propagation effects make optical fibre channels very different from traditional linear communications channels such as wireless or copper cables. There is a clear need for radically different methods for the coding, transmission, and processing of information that take the nonlinear properties of the optical fibre into account. The nonlinear Fourier transform (NFT) that is to be used in place of the conventional Fourier transform, offers new opportunities for the development of fundamentally novel engineering techniques for the coding, modulation, transmission, and processing of information in optical fibre channels. The student will work on the theoretical development and experimental verification of new coding and modulations techniques for NFT-based optical transmission systems under the supervision of world-class mentors: Prof. S. Turitsyn (AIPT, main supervisor), Drs Y. Prylepskiy (AIPT), H. Buelow (NBL), and M. Yousefi (TPT). FONTE ESRs will benefit from cross-disciplinary joint supervision by world experts in optical communication in academia and industry.

Person Specification
FONTE is looking for candidates with exceptional skills in signal processing, optical communication or applied mathematics. Preferred skill requirements include experience in experimental work, knowledge of scientific programming and computing, physical optics, communications. Knowledge in differential equations, mathematical physics, numerical analysis, information and communication theory, or machine learning is an asset. Applicants with a Master of Science degree in Electrical Engineering, Applied Mathematics, Physics, or equivalent, are especially encouraged to apply. The successful applicant should have a first class or upper second class honours degree or equivalent qualification in engineering or physics.

For informal enquiries about this project and other opportunities within the AIPT, contact Prof. Sergei Turitsyn by email: s.k.turitsyn@aston.ac.uk

If you require further information about the application process please contact the Postgraduate Admissions team at seasres@aston.ac.uk

Additional Requirements

1. Academic Entry Requirements
You should have been awarded, or expect to achieve, a first or upper second class Honours degree or equivalent qualification in engineering or physics. Preferred skill requirements include experience in experimental work, knowledge of scientific programming and computing, physical optics, communications. If your qualifications are from an overseas institution please provide transcripts of the marks you have already achieved with your application.

2. English language
For applicants from non-English speaking countries, it is necessary to have taken either the Test of English as a Foreign Language (TOEFL) or the British Council IELTS test (taken no more than two years before the start date of your course). Minimum requirements are: TOEFL IBT: 93 (23 in Writing, 19 in Speaking, 18 in Reading and 19 in Listening) IELTS: 6.5 (6.0 in Writing Speaking, Reading and Listening). Pearsons English language test: 63 with no less than 57 in each band

Further information can be found at http://www.aston.ac.uk/eas/research/prospective-research-students/how-to-apply/

3. MSCA Eligibility
Applicants must be Early Stage Researchers (ESR), i.e. be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree. Full-time equivalent research experience is measured FROM the date when the researcher obtained the degree entitling him/her to embark on a doctorate (either in the country in which the degree was obtained or in the country in which the researcher is recruited) – even if a doctorate was never started or envisaged. Research Experience is measured TO the first day of the FONTE employment contract of the researcher.

4. MSCA Mobility
Researchers may not have resided or carried out their main activity (work, studies, etc.) in the UK for more than 12 months in the 3 years immediately before the recruitment date.

Interested candiidates should contact Prof Sergei Turitsyn [s.k.turitsyn@aston.ac.uk]  in the first instance.

PhD Studentships in Signal Processing Techniques
 
Programe of Electrical Engineering,  Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil
 
Applications are invited for PhD studentships in signal processing techniques. These studentships are funded by the CNPq/CAPES research councils in Brazil. The topic of the project is open in the broad area of signal processing techniques. Potential topics include:
- Adaptive signal processing algorithms
- Distributed signal processing techniques
- Array signal processing: beamforming, direction finding and localization
- Detection and estimation algorithms
- Sparsity-aware and compressive sensing algorithm

The application areas are: wireless communications, wireless sensor networks, internet of things (IoT) and radar and sonar systems
 
Deadline for application: 29th June 2018
Start date: mid August 2018
 
The activities will involve the development of system and signal models using linear algebra, simulation tools, development signal processing algorithms and analytical approaches.
 
This is an exciting international opportunity for candidates with (or expecting) an MEng or an MSc with First Class Honours in Electrical and Electronic Engineering or related areas. Amongst the key technical disciplines are an excellent level of mathematics, development of algorithms and design of sensor array systems. The successful candidates will be based at the PUC-Rio, Rio de Janeiro, Brazil, will visit international partners, and is expected to attend international conferences and collaborate extensively with international experts.
 
The studentships are open to everyone, cover the tuition fees, and give a stipend of about US$ 850 per month for 4 years subject to an annual increase. Additional funding might be available with industrial projects and requires extra 4-6 hours per week. 
 
Applicants should send an up to date CV with photo, a one-page personal statement, full contact details (including email addresses) of 2 referees, transcripts and publications to:
 
Prof. Rodrigo C de Lamare (http://delamare.cetuc.puc-rio.br/) - delamare@cetuc.puc-rio.br

Salary: GBP 30,688 to GBP 38,833 per annum
Closing Date: 1 May 2018 (23:00 BST)
https://jobs.surrey.ac.uk/021518

Applications are invited for a Research Fellow in Machine Listening to work full-time on an EPSRC-funded project "Making Sense of Sounds", to start as soon as possible, for 9.75 months until 13 March 2019. This project is investigating how to make sense from sound data, focussing on how to allow people to search, browse and interact with sounds. The candidate will be responsible for investigating and developing machine learning methods for analysis of everyday sounds, leading to new representations to support search, retrieval and interaction with sound.

The successful applicant is expected to have a PhD or equivalent in electronic engineering, computer science or a related subject, and is expected to have significant research experience in audio signal processing and machine learning. Research experience in one or more of the following is desirable: deep learning; blind source separation, blind de-reverberation, sparse and/or non-negative representations, audio feature extraction.

The project is being led by Prof Mark Plumbley in the Centre for Vision Speech and Signal Processing (CVSSP) at the University of Surrey, in collaboration with the Digital World Research Centre (DWRC) at Surrey, and the University of Salford. The postholder will be based in CVSSP and work under the direction of Prof Plumbley and Co-Investigators Dr Wenwu Wang and Dr Philip Jackson. For more about the project see: http://cvssp.org/projects/making_sense_of_sounds/

CVSSP is an International Centre of Excellence for research in Audio-Visual Machine Perception, with 125 researchers, a grant portfolio of £20M. The Centre has state-of-the-art acoustic capture and analysis facilities enabling research into audio source separation, music transcription and spatial audio. Audio-visual compute includes 700 cores and a 50GPU machine learning cluster with 500TB of online storage.

Informal enquires are welcome, to: Prof Mark Plumbley (m.plumbley@surrey.ac.uk), Dr Wenwu Wang (w.wang@surrey.ac.uk), or Dr Philip Jackson (p.jackson@surrey.ac.uk).

For more information and to apply online, please visit:

https://jobs.surrey.ac.uk/021518

We acknowledge, understand and embrace diversity.

The Faculty of Information Technology and Electrical Engineering, at the Norwegian University of Science and Technology (NTNU) has two (2) PhD Research Fellow vacancies at the Department of Electronic Systems (IES).

Each of the PhD positions is for up to 4 years with 25% work assignments for NTNU IES.

Project Description

The pervasion of the Internet of Things (IoT) which connects numerous sensors, actuators, appliances, vehicles etc., will have a strong impact on the evolution of smarter and greener cities as well as on environmental monitoring. A basic tenet underlying all key functionalities of the IoT is situational awareness, i.e., the ability to capture events and derive accurate, critical information to facilitate decision making for timely actions in a heterogeneous and highly dynamic environment. The scale and largely interconnected nature of IoT, together with the stringent requirements on low energy and limited hardware, pose severe challenges to security. The network of IoT is vulnerable to various forms of man-made intrusion or natural disruption. For example, an adversary may gain full control over a subset of the devices, and maliciously alter the reported measurements. This calls for an intelligent infrastructure that is autonomous, dependable, and resilient to natural or man-made disturbances. To ensure that the IoTs operate effectively, we need to take a holistic approach to designing secure sensor networks with resource-efficient functional algorithms starting with sensing, followed by data processing and communication to ensure reliable decision making for long long-lasting, secure, and dependable services.

The PhD projects will be around developing and analyzing new efficient distributed detection, estimation and (machine) learning schemes to improve data quality and security of the physical-layer signals in IoT. The aim is to go beyond the state-of-the-art solutions and take a holistic approach encompassing intelligent sensors, smart inference, and secure two-way communication among all the devices in the network.

The application

More information and for the application submission, please click this link. Please submit an application letter describing your motivation, relevant experience, skills and qualifications, and a brief research vision for the position (maximum 2 pages) along with a CV, publication list, letters of reference and proof of fluency in the English language (if applicable) and certificates from both Bachelor and Master degrees.

Applicants are kindly requested to send a diploma supplement or a similar document, which describes in detail the study and grading system and the rights for further studies associated with the obtained degree.
Incomplete applications will not be taken into consideration

Formalities

The appointment is made in accordance with the regulations of employment for PhD candidates issued by the Ministry of Education and Research, with relevant parts of the additional guidelines for appointment as a PhD candidate at NTNU. Applicants must participate in an organized PhD programme of study during their period of employment. The candidate appointed must comply with the regulations for employees in the public sector. In addition, a contract will be signed regarding the period of employment.

Applicants must be qualified for admission to a PhD study program at NTNU. See http://www.ntnu.no/ie/forskning/phd for information about PhD studies at NTNU.

We can offer

• an informal and friendly workplace with dedicated colleagues
• academic challenges in a cross-disciplinary team
• attractive schemes for home loans, insurance and pensions through the Norwegian Public Service Pension Fund

Depending on qualifications and academic background, PhD Candidates (in code 1017) at the Faculty of Information Technology and Electrical Engineering will be remunerated at a minimum of NOK 436 500 per year before tax. Normal wage level is NOK 436 500 of which 2% is deducted for the Norwegian Public Service Pension Fund. The appointment is subject to the conditions in effect at any time for employees in the public sector.

The Faculty of Information Technology and Electrical Engineering, at the Norwegian University of Science and Technology (NTNU) has one Postdoctoral Research vacancy at the Department of Electronic Systems (IES). The postdoctoral position is for two (2) years.

Project Description

In Internet-of-things (IoT), as sensing and estimation becomes more distributed, sensors/estimators will need to communicate with each other and other entities in the network to obtain an accurate picture of the system being observed. In a distributed IoT/wireless sensor network, the sensor nodes share their observations with the neighboring nodes and cooperate to enhance the accuracy of the inference. As the number of sensors increases, the amount of data that will be stored, processed and communicated increases dramatically so that system throughput and latency will not be adequate to ensure reliable and secure operation. In this project we are particularly interested in the development of new methods and algorithms that enable frugal usage of energy by the sensors, that can effectively convert the data collected by myriads of sensors into actionable intelligence, and that are robust and resilient to malfunctioning sensors or malicious disturbance.

The candidate will conduct research together with personnel in the group of Prof. Stefan Werner, as well as researchers connected to the NTNU Internet-of-things lab. Preference will be given to candidates who can work independently and have a strong potential to build competence and guide students within the following research areas:

1. Decentralized statistical learning for energy-efficient sensor networks in IoT
2. Graph signal processing in IoT
3. Distributed optimization with applications to IoT/wireless sensor networks

We search for candidates with keen interests in these tasks, and those with the best qualifications will be invited for an interview.

Qualifications

The candidate is expected to be able to work independently, have a solid mathematical background and a PhD in statistical signal processing, applied mathematics, statistics or machine learning, wireless sensor networks, electrical engineering, or related field. Good command in English language (spoken and written) is a prerequisite. An eligible candidate should have submitted the PhD thesis for assessment by the application deadline.

The application

More information and for the application submission, please click this link. The following documents need to be attached in the application:

• A brief research statement, describing the candidate’s research interests and plans, and publication plan (maximum 3 pages in total)
• CV as PDF including a full list of publications with bibliographical references Indicate the most important publications that are relevant for the evaluation of the applicant’s qualifications (maximum 10 publications).
• Testimonials and certificates
• Other documents which the applicant would find relevant

Incomplete applications will not be taken into consideration.

We can offer

• an informal and friendly workplace with dedicated colleagues
• academic challenges in a cross-disciplinary team
• attractive schemes for home loans, insurance and pensions through the Norwegian Public Service Pension Fund

For further information about the position, contact Professor Stefan Werner, email: stefan.werner@ntnu.no

Depending on qualifications and academic background, postdoctoral fellows (1352) will be remunerated at a minimum of NOK 490 500 per year before tax and the position as. There will be a 2 % deduction to the Norwegian Public Service Pension Fund from gross wage. The appointment is subject to the conditions in effect at any time for employees in the public sector.