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Postdoc in Mathematical Biology at Univ. Sydney

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Location: School of Mathematics and Statistics, The University of Sydney
Employment Type: Full time 2 year fixed term
Duration: 2 years fixed term appointment
Remuneration: $97,043–$100,717 p.a. + 17% superannuation (Level A)
Closing Date: 11.59pm; 13 August 2023

About the opportunity

We are seeking to appoint a Postdoctoral Research Associate in Mathematical Biology (with a focus on modelling the immune system) to conduct innovative research in mathematical and computational modelling of immune system dynamics. The position will be under the supervision of Prof Peter Kim (University of Sydney).

Some of your responsibilities will be to:

• work under the supervision of Prof Peter Kim in collaboration with Prof Federico Frascoli (Swinburne University of Technology), Dr Robyn Araujo (Queensland University of Technology), and Prof Peter Lee (City of Hope and Beckman Research Institute, Duarte, USA)
• develop mathematical and computational models of immune dynamics
• write scholarly papers for publication in academic journals
• present research at seminars, conferences, and workshops
• teach undergraduate courses (approximately 26 lecture hours and 24 tutorial hours per year)

This position has been made possible by the awarding of an Australian Research Council Discovery Project to chief investigators Prof Peter Kim (University of Sydney), Prof Federico Frascoli (Swinburne University of Technology), Dr Robyn Araujo (Queensland University of Technology), and partner investigator Prof Peter Lee (City of Hope and Beckman Research Institute, Duarte, USA).

To learn more about the School of Mathematics and Statistics click here.

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Pre-employment checks

Your employment is conditional upon the completion of all roles required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

How to apply

Learn more about this position and apply: https://usyd.wd3.myworkdayjobs.com/USYD_EXTERNAL_CAREER_SITE/job/Darlington-Campus/Research-Associate-in-Mathematical-Biology–with-a-focus-on-Modelling-the-Immune-System-_0105303-1.

Learning Success Advisor @Sydney

/in , /by

Location: Student Support Services, The University of Sydney, Camperdown Campus
Employment Type: Full time
Duration: continuing
Remuneration: Base Salary $100,032–$108,979 + 17% superannuation
Closing Date: 11.59pm; 17 July 2023

• Exciting opportunity to facilitate and deliver mathematics and statistics learning support for students at the University

About the opportunity

As a Learning Success Adviser (Mathematics), you will act as an integral member of a team of specialist professional staff focusing on student facing support. You will be working in a fast-paced environment where you will help develop, deliver, and evaluate mathematics and statistics learning support initiatives for all students at the University. You will play a pivotal role in contributing to the University’s strategic initiatives for the provision of learning support.

As a subject matter specialist, you will collaborate in the development and implementation of learning support initiatives, including student-centred learning design, personalised and adaptive support offerings, through a variety of delivery modes such as face to face, online, blended, hybrid and peer-facilitated.

Your key responsibilities will be to:

• help students to develop their confidence in mathematics and statistical skills, enhancing their experience and supporting fuller participation and success in relevant units of study.
• deliver learning support & training activities to students, peer-facilitators, & staff for up to 20 hours a week
• work within a dynamic team, reporting to the Learning Hub Lead
• deliver learning support & training activities to students, peer-facilitators, & staff for up to 20 hours a week
• work collaboratively with the Learning Hub Lead, and collaboratively with other Learning Success Advisors, the Ed Services team, and colleagues across CET + Learning Hub • provide guidance and support to relevant stakeholders in relevant faculties, library, Educational Innovation, Student Life, and the wider Education Portfolio
• engage in and contribute to continuing professional development within the CET + Learning Hub unit and externally to ensure implementation of best practice in mathematics and numeracy learning support and maintain current knowledge of the high school and relevant University-level curricula
• contribute to and engage actively with the mathematics and statistics learning community beyond the University to further the reputation of the University in the field.

About you

• a strong background and experience in tertiary mathematics and/or statistics (post graduate qualifications and/or relevant work experience in a related field are highly desirable)
• experience in teaching and learning in a tertiary environment, with an emphasis on settings relevant to mathematics and statistics support
• experience in developing and facilitating high-quality, innovative programs to support mathematics and statistics learning in a higher education environment
• experience using learning analytics to inform learning design, support student progress and monitor student outcomes
• experience using innovative educational technology platforms to facilitate mathematics and statistics support to diverse cohorts of students
• theoretical and practical understanding of effective educational practice in the higher education space, including the use of educational technologies.

This will be a continuing appointment. The successful candidate will be offered a competitive remuneration package commensurate with the responsibilities of the position and the candidate’s relevant experience and qualifications.

Other

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Sponsorship / work rights for Australia

Please note: Visa sponsorship is not available for this position. For a continuing position, you must be an Australian or New Zealand citizen or an Australian Permanent Resident.
Australian Temporary Residents currently employed at the University of Sydney may be considered for a fixed term contract for the length of their visa, depending on the requirements of the hiring area and the position.

Pre-employment checks

Your employment is conditional upon the completion of all roles required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

This position is designated as involving child-related work. To undertake or remain in this position, you are required to apply for and obtain a Working with Children Check clearance in accordance with the Child Protection (Working with Children) Act 2012.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

How to apply

Apply via this link: https://usyd.wd3.myworkdayjobs.com/USYD_EXTERNAL_CAREER_SITE/job/Darlington-Campus/Learning-Success-Advisor–Mathematics-_0106000-2

For a confidential discussion about the role, or if you require reasonable adjustment, or any documents in alternate formats, please contact Felicity Appleby, Recruitment Operations by email to recruitment.admin@sydney.edu.au.

© The University of Sydney

The University reserves the right not to proceed with any appointment.

Research Associate in Statistical Bioinformatics@Sydney

/in , /by

Location: Camperdown Campus at the School of Mathematics and Statistics, The University of Sydney
Employment Type: Full time
Duration: 18 months fixed term appointment
Remuneration: $79,784–$107,516 p.a. + 17% superannuation (Level A)
Closing Date: 11.59pm; 30 May 2023

• Full time 18 month fixed term, located on the Camperdown Campus at the School of Mathematics and Statistics
• Opportunity to make valuable contributions to research in statistical bioinformatics and biomedical data science

About the opportunity

We are one of the largest mathematical sciences schools in Australia, and the University of Sydney is the only Australian university to have received the highest rating of 5 out of 5 for research in the mathematical sciences in every Australian Research Council Excellence in Research for Australia assessment to date. The University also hosts the Sydney Mathematical Research Institute (SMRI), which attracts leading mathematical scientists from all over the world to do research with Australian collaborators.

We are seeking to appoint a Postdoctoral Research Associate to work on a project entitled ‘Multiscale data integration for single cell spatial genomics’. The successful candidate will work under the supervision of Dr Shila Ghazanfar on developing new statistical and algorithmic techniques to understand single cell spatial genomics data. This project has recently been funded by the Chan Zuckerberg Initiative.

Technological advances in measuring gene expression in a spatially resolved manner have resulted in several tour-de-force publicly available datasets, often accompanied by sample-matched dissociated single cell RNA-seq or single cell multi-omic measurements. However, many integrative data analysis tasks for spatial genomics are performed using tools designed with dissociated single cell RNA-seq data in mind, effectively ignoring the specific data structures of spatial genomics data. This project will develop new data science techniques for multiscale data integration of single cell spatial genomics, with applications in several collaborative contexts.

Your key responsibilities will be to:

• undertake research in statistical bioinformatics for single cell spatial genomics
• publish research papers
• demonstrate research excellence
• assist with grant writing and publishing original work
• participate in research group meetings and other activities
• formulate and refine statistical and computational methods for single cell spatial genomics data integration
• develop software using the R language and contribute to Bioconductor.

The School of Mathematics and Statistics of the University of Sydney is one of the largest in Australia. It has more than 89 academic staff to supervise research and teaching 74 postgraduate students and 925 equivalent full-time student-load undergraduate students.

To learn more about the School of Mathematics and Statistics click here.

About you

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for a Research Associate who has:

• demonstrated ability to conduct research/scholarly activities under limited supervision
• the ability and a willingness to collaborate in multidisciplinary teams to contribute to long-term research goals
• a strong track record of publishing their research
• research strengths in state-of-the-art high dimensional analysis of complex data
• superior computer programming or software development skills in R or similar
• excellent communication (written and verbal), organisational and problem-solving skills with attention to detail
• a high level of interpersonal skills, including the ability to work collaboratively with colleagues
• a demonstrated ability to complete work in timely fashion and to write up results for publication
• a PhD (or near completion) in bioinformatics, data science, computer science, computational biology and equivalent combination of training and experience

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Pre-employment checks

Your employment is conditional upon the completion of all roles required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

How to apply

Learn more about this position and apply: https://usyd.wd3.myworkdayjobs.com/en-US/USYD_EXTERNAL_CAREER_SITE/job/Research-Associate-in-Statistical-Bioinformatics_0105459-2.

PhD scholarship: Mathematical Optimization @Sydney

/in , /by

Closing date: 31 May 2023
Campus: University of Sydney, Discipline of Business Analytics
Remuneration: $37,207 (indexed yearly) per annum
Status: 3.5 years with possible 6 month extension 

The PhD Scholarship in Mathematical Optimization within the Discipline of Business Analytics at the University of Sydney will support an outstanding research student to undertake doctoral studies in mathematical optimization.

Potential research topics will be on mathematical optimization broadly defined, and could include theory and algorithms for continuous optimization, stochastic programming, robust/distributionally robust optimization and data-driven optimization, with applications to machine learning, statistics, finance and economics.

The scholarship includes tuition and a living allowance of up to $37,207 (indexed yearly) for up to 3.5 years, with the possibility of a six-month extension subject to approval.

Requirements

You must:

  • be a domestic or international student
  • have an unconditional offer of admission to undertake PhD on a full-time basis at the University of Sydney Business School
  • hold an Honours degree (First Class) or a First Class Honours Equivalent Degree or a Master’s degree with a substantial research component in a relevant area of study
  • be willing to conduct research under the supervision of Dr Nam Ho-Nguyen.

How to apply

We invite applicants to send the following material via email to:
Dr Nam Ho-Nguyen (nam.honguyen@sydney.edu.au):

  • An up-to-date CV/resume.
  • Copies of academic transcripts.
  • Name, affiliation and email of two academic referees. We will notify applicants before contacting referees.
  • (Optional) A short (2 page maximum) statement of purpose.

Information: https://www.sydney.edu.au/scholarships/a/the-phd-scholarship-in-mathematical-optimization.html

Learning Success Advisor @Sydney

/in , /by

Location: School of Mathematics and Statistics, The University of Sydney, Camperdown Campus
Employment Type: Full time until 22 December 2023
Duration: fixed term
Remuneration: Base Salary $100,032–$108,979 + 17% superannuation
Closing Date: 11.59pm; 20 March 2023

• Exciting opportunity to facilitate and deliver mathematics and statistics learning support for students at the University
• 2x Full-time, fixed term until 22nd December 2023

About the opportunity

As a Learning Success Adviser (Mathematics), you will help develop, deliver, and evaluate mathematics and statistics learning support initiatives for all students at the University.

As a subject matter specialist, you will collaborate in the development and implementation of learning support initiatives, including student-centred learning design, personalised and adaptive support offerings, through a variety of delivery modes such as face to face, online, blended, hybrid and peer-facilitated.

Your key responsibilities will be to:

• work within a dynamic team, reporting to the Learning Hub Lead
• deliver learning support & training activities to students, peer-facilitators, & staff for up to 20 hours a week
• work collaboratively with the Learning Hub Lead and team of Learning Success Advisors, Educational Designer, and colleagues across CET + Learning Hub
• contribute to and engage actively with the mathematics and statistics learning community beyond the University to further the reputation of the University in the field
• provide specialist guidance and support to relevant stakeholders in the library, relevant faculties, Educational Innovation, Student Life, and the wider Education Portfolio
• help students to develop their confidence in mathematics and statistical skills, enhancing their experience and supporting fuller participation and success in relevant units of study.

About you

• post graduate qualifications and/or relevant work experience in a related field
• a strong background and experience in tertiary mathematics and/or statistics
• experience in teaching and learning in a tertiary environment, with an emphasis on settings relevant to mathematics and statistics support
• experience in developing and facilitating high-quality, innovative programs to support mathematics and statistics learning in a higher education environment
• experience using learning analytics to inform learning design, support student progress and monitor student outcomes
• experience using innovative educational technology platforms to facilitate mathematics and statistics support to diverse cohorts of students
• theoretical and practical understanding of effective educational practice in the post-entry, higher education space, including the use of educational technologies.

This will be a continuing appointment. The successful candidate will be offered a competitive remuneration package commensurate with the responsibilities of the position and the candidate’s relevant experience and qualifications.

Other

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Sponsorship / work rights for Australia

Please note: Visa sponsorship is not available for this position. For a continuing position, you must be an Australian or New Zealand citizen or an Australian Permanent Resident.
Australian Temporary Residents currently employed at the University of Sydney may be considered for a fixed term contract for the length of their visa, depending on the requirements of the hiring area and the position.

Pre-employment checks

Your employment is conditional upon the completion of all roles required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

This position is designated as involving child-related work. To undertake or remain in this position, you are required to apply for and obtain a Working with Children Check clearance in accordance with the Child Protection (Working with Children) Act 2012.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

How to apply

Apply via this link: https://usyd.wd3.myworkdayjobs.com/USYD_EXTERNAL_CAREER_SITE/job/Darlington-Campus/Learning-Success-Advisor–Mathematics-_0101673-3

For a confidential discussion about the role, or if you require reasonable adjustment, or any documents in alternate formats, please contact Kale Claffey, Recruitment Operations by email to kale.claffey@sydney.edu.au.

© The University of Sydney

The University reserves the right not to proceed with any appointment.

Postdoctoral Research Associate in Statistical Bioinformatics@Sydney

/in , /by

Location: Camperdown Campus at the School of Mathematics and Statistics, The University of Sydney
Employment Type: Full time
Duration: 18 months fixed term appointment
Remuneration: $97,043–$100,717 p.a. + 17% superannuation (Level A)
Closing Date: 11.59pm; 6 February 2023

• Full time 18 month fixed term, located on the Camperdown Campus at the School of Mathematics and Statistics
• Opportunity to make valuable contributions to research in statistical bioinformatics and biomedical data science

About the opportunity

We are one of the largest mathematical sciences schools in Australia, and the University of Sydney is the only Australian university to have received the highest rating of 5 out of 5 for research in the mathematical sciences in every Australian Research Council Excellence in Research for Australia assessment to date. The University also hosts the Sydney Mathematical Research Institute (SMRI), which attracts leading mathematical scientists from all over the world to do research with Australian collaborators.

We are seeking to appoint a Postdoctoral Research Associate to work on a project entitled ‘Multiscale data integration for single cell spatial genomics’. The successful candidate will work under the supervision of Dr Shila Ghazanfar on developing new statistical and algorithmic techniques to understand single cell spatial genomics data. This project has recently been funded by the Chan Zuckerberg Initiative.

Technological advances in measuring gene expression in a spatially resolved manner have resulted in several tour-de-force publicly available datasets, often accompanied by sample-matched dissociated single cell RNA-seq or single cell multi-omic measurements. However, many integrative data analysis tasks for spatial genomics are performed using tools designed with dissociated single cell RNA-seq data in mind, effectively ignoring the specific data structures of spatial genomics data. This project will develop new data science techniques for multiscale data integration of single cell spatial genomics, with applications in several collaborative contexts.

Your key responsibilities will be to:

• undertake research in statistical bioinformatics for single cell spatial genomics
• publish research papers
•

demonstrate research excellence
• assist with grant writing and publishing original work
• participate in research group meetings and other activities
• formulate and refine statistical and computational methods for single cell spatial genomics data integration
• develop software using the R language and contribute to Bioconductor.

The School of Mathematics and Statistics of the University of Sydney is one of the largest in Australia. It has more than 89 academic staff to supervise research and teaching 74 postgraduate students and 925 equivalent full-time student-load undergraduate students.

To learn more about the School of Mathematics and Statistics click here.

About you

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for a Postdoctoral Research Associate who has:

• a PhD (or near completion) in bioinformatics, data science, computer science, computational biology and equivalent combination of training and experience
• demonstrated ability to conduct research/scholarly activities under limited supervision
• the ability and a willingness to collaborate in multidisciplinary teams to contribute to long-term research goals
• a strong track record of publishing their research
• research strengths in state-of-the-art high dimensional analysis of complex data
• superior computer programming or software development skills in R or similar
• excellent communication (written and verbal), organisational and problem-solving skills with attention to detail
• a high level of interpersonal skills, including the ability to work collaboratively with colleagues
• a demonstrated ability to complete work in timely fashion and to write up results for publication.

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Pre-employment checks

Your employment is conditional upon the completion of all roles required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

How to apply

Learn more about this position and apply: https://usyd.wd3.myworkdayjobs.com/en-US/USYD_EXTERNAL_CAREER_SITE/job/Postdoctoral-Research-Associate-in-Statistical-Bioinformatics_0100807-2https://usyd.wd3.myworkdayjobs.com/en-US/USYD_EXTERNAL_CAREER_SITE/job/Postdoctoral-Research-Associate-in-Statistical-Bioinformatics_0100807-2.

Postdoctoral Research Associate in Mathematics (Dynamical Systems and Machine Learning) @Sydney

/in , /by

Location: Camperdown Campus at the School of Mathematics and Statistics, The University of Sydney
Employment Type: Full time 2 year fixed term
Duration: 2 years fixed term appointment
Remuneration: $97,043–$100,717 p.a. + 17% superannuation (Level A)
Closing Date: 11.59pm; 22 February 2023

• Full time, 2 years fixed term, located located on the Camperdown Campus
• Opportunity to make valuable contributions to research at the interface between dynamical systems and machine learning

About the opportunity

We are seeking to appoint a Postdoctoral Research Associate to work on a project entitled “A dynamical systems theory approach to machine learning”. The successful candidate will work under the supervision of Professor Georg Gottwald on developing, understanding and applying machine learning techniques using tools from dynamical systems theory. This project has recently been funded by the Australian Research Council.

Forecasting the future state of a high-dimensional complex multi-scale system is a challenge we face in areas ranging from climate science to epidemiology. Even when basic physical mechanisms have been identified, the actual evolution equations are often unknown. This project will develop a computationally cheap machine learning framework for forecasting. We will develop mathematical theory underpinning the novel methodology, as well as applying it to the perennial problem of subgrid-scale parametrisation in climate modelling. Furthermore, we will apply dynamical systems theory to understand existing machine learning algorithms.

Your key responsibilities will be to:

• undertake research at the interface between dynamical systems and machine learning
• publish research papers
• demonstrate research excellence.

The School of Mathematics and Statistics of the University of Sydney is one of the largest in Australia. It has more than 89 academic staff to supervise research and teaching 74 postgraduate students and 925 equivalent full-time student-load undergraduate students.

To learn more about the School of Mathematics and Statistics click here.

About you

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for a Postdoctoral Research Associate in Mathematics and AI who has:

• a PhD (or near completion) in mathematics or a relevant area
• relevant expertise in dynamical systems and machine learning desired
• demonstrated ability to conduct research/scholarly activities under limited supervision
• the ability and a willingness to collaborate in multidisciplinary teams to contribute to long-term research goals
• a strong track record of publishing their research
• excellent communication (written and verbal), organisational and problem-solving skills with attention to detail
• high level interpersonal skills, including the ability to work collaboratively with colleagues
• a demonstrated ability to complete work in timely fashion and to write up results for publication.

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Pre-employment checks

Your employment is conditional upon the completion of all roles required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

How to apply

Learn more about this position and apply: https://usyd.wd3.myworkdayjobs.com/USYD_EXTERNAL_CAREER_SITE/job/Camperdown-Campus/Postdoctoral-Research-Associate-in-Mathematics–Dynamical-Systems-and-Machine-Learning-_0101102-1.