About the team:

The Data Science team at Xandr is responsible for driving algorithmic product innovation across the company.  Our projects underlie major features for both buyers and sellers on our platform, as well as the marketplace design for our ad exchange itself. We combine elements of theory with the practical tools and techniques for exploring vast quantities of data, all with the aim of designing effective algorithms to achieve product goals. Data Science partners closely with Engineering, Product, and Data Analytics to ensure that our solutions are solving the right business problem, are scaling as needed, and are achieving the expected results for our clients.

As a team, we have diverse set of backgrounds (math, physics, engineering, operations research, statistics, econometrics, political science) and a spectrum of credentials (about half have PhDs). Our culture centers on collaborating, continuously learning and teaching, and producing effective solutions for our users, whether they rely on elegant theory or on simple heuristics and empirical evidence. We love that our contributions further Xandr’s position as a pioneer and thought leader in the AdTech industry, but we measure our efforts based on the impact and value we create for our clients and internal teammates.

The Data Scientist role is perfect for someone who is passionate about combining deep technical understanding, broad domain knowledge, and creative problem-solving skills to design products that make a measurable impact for our users.

About the job:

  • Use machine learning techniques, visualizations, statistical analysis, etc. to gain insight into various data sets – some of which are readily available, and some of which you create and curate yourself
  • Participate in the full lifecycle of algorithm-based feature development: researching and designing solutions, running tests with clients and performing deep analyses to understand results, implementing scalable solutions in production environments, and monitoring platform-wide impact
  • Collaborate with team members, both to build out specific projects and to continuously teach and learn new technology and techniques
  • Communicate findings and solutions clearly to a variety of audiences, e.g. writing clear, comprehensive specs for engineers or explaining algorithmic concepts to product managers
  • Actively seek out a broad understanding of the Xandr platform and products, and align design efforts with that context
  • Work independently with minimal supervision but high accountability

 

About your skills and experience:

  • PhD in a relevant quantitative field, or 1-3 years relevant applied research or industry experience
  • Basic programming experience – we primarily use Python and SQL, but you may have experience in R, MATLAB, or another language
  • Experience with machine learning techniques is a plus
  • Proven excellence at formulating, understanding, and solving complex, non-routine quantitative problems
  • Aptitude for learning new theory and new technology
  • Strong written and verbal communication skills
  • Hands-on attitude toward problem-solving, including a willingness to dig into terabytes of data and quickly construct tools or models
  • Ability to work in a highly interactive, collaborative, fluid environment

More about you:

  • You are passionate about a culture of learning and teaching. You love challenging yourself to constantly improve, and sharing your knowledge to empower others
  • You are relentless when looking for solutions to complex problems, and your grit serves you well when analyzing and debugging the root cause of unexpected results
  • You care about solving big, systemic problems. You look beyond the surface to understand root causes so that you can build long-term solutions for the whole ecosystem
  • You believe in not only serving customers, but also empowering them by providing knowledge and tools

About the team

The mission of Zillow Group’s Relevance Personalization team is to help customers discover their next home through relevant & delightful product experiences and messaging. We power those customer experiences through a deep understanding of our customers, the homes they love, and machine learning. Our team powers a variety of major personalized customer touchpoints such as personalized search ranking, similar homes recommendations, or email and push notification messaging on both Zillow and Trulia brands. In the past several years our team has been growing its impact on Zillow’s business, and we are looking to proliferate personalization into new product areas and business domains. Our internal businesses partners include the Premier Agent business helping buyers find the right home, the Zillow Offers business making it easy for sellers to move to the next home more seamlessly, and New Construction.

 

About the role

Zillow is actively seeking an outstanding research intern who is studying computer science, statistics, applied mathematics, econometrics, or a related scientific subject area involving mathematical modeling to join our team for the summer of 2021. Machine Learning has huge impacts across virtually all of Zillow’s business lines, and as an embedded member of one of these teams, you will have the opportunity to apply groundbreaking research techniques to high-stakes business problems. You will conduct this research in a collaborative environment where you will have the chance to get frequent feedback on your ideas and provide insight into the work of other teammates.

 

As an intern, you will have the opportunity to:

  • Collaborate with other Applied Scientists and Software Developers to conduct cutting-edge applied research
  • Find insights in diverse datasets and use those signals by applying and developing state of the art machine learning and statistical techniques.
  • Work closely with Software Developers to learn how to productionalize and ship those models.

 

The following recently published blog posts provide examples of our team’s work:

This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice which must be identified to the Company. Employees may live in any of the 50 US States, with limited exceptions. In certain cases, an employee in a remote-designated job may need to live in a specific region or time zone to support customers or clients as part of their role.

 

Who you are

  • In the process of completing a Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Econometrics, or a related scientific subject area involving mathematical modeling (preferred) with a graduation date between Dec 2021 and Summer 2022
  • Experienced working in Python to conduct detailed data analysis, visualization, and modeling
  • Excited to look for insights in data and conduct feature engineering to and to use those signals in new ML and statistical models
  • Proficient at using algorithms for supervised or unsupervised learning with an interest in contributing to and extending open source libraries
  • Able to conduct research, assimilate state-of-the-art methods from research papers, and turn product requirements into algorithmic solutions.
  • Able to clearly present and communicate research to both technical and non-technical audiences
  • Able to work on a team in a collaborative environment to tackle ambitious machine learning problems
  • Develop new techniques, contribute to writing papers and or blog posts to show off your novel work, giving back to the larger Machine Learning community.

 

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

 

Get to know us

The Data Science & AI group in Personal System Software is responsible for delivering a broad range of software capabilities, including generating actionable insights from business data, increasing operational efficiency with automation, and building breakthrough experiences for HP products and services. We are seeking Machine Learning engineer to collaborate with our software engineers and product teams to solve difficult technical problems and develop new machine learning capabilities that will impact upcoming HP products. If you have deep technical skills, are intensely curious, and like to attack the hardest and the most challenging problems, want to make a difference in the lives of others, and want to work in a highly supportive environment, then we invite you to apply to join our team.

In this highly visible role, you will:

  • Work in all phases of building, deploying, and evaluating machine learning applications
  • Lay the foundation for new products and services by developing new technical solutions to difficult problems.
  • Work in a cross-functional team environment.
  • Communicate your results internally within Personal System software.

Some of our areas of interest include:

(1) Machine Vision, including demographics analysis, people tracking, object recognition, and scene understanding

(2) Predictive Analytics, including failure prediction, time-series forecasting, anomaly detection, and root cause analysis

(3) Recommendation systems, including content customization and customer engagement improvement

(4) Natural Language Processing, including sentiment analysis, text summarization, and conversational interfaces

(5) MLOps, along with integration with software development lifecycles and continuous integration/continuous delivery

Responsibilities

  • Mines data using modern tools and programming languages.
  • Defines and implements models to uncover patterns and predictions creating business value and innovation.
  • Works with the business to understand the business domain perspective.
  • Effectively tells stories with the data using visualization tools/methods to demonstrate insight impact and business value.
  • Assures accuracy, integrity, and compliance of cleansed data.
  • Maintains proficiency within the data science domain by keeping up with technology and trend shifts.
  • Leads a project team of data science professionals, assuring insights are communicated regularly and effectively, reviewing designs, models, accuracy and data compliance.
  • Collaborates and communicates with the project team regarding project progress and issue resolution.
  • Represents the data science team for all phases of larger and more-complex development projects.
  • Provides guidance, training, and mentoring to less experienced staff members.

Knowledge & Skills

Minimum:

  • Extensive experience using statistics, mathematics, algorithms, and programming languages.
  • Possess a background in linear algebra, statistics, or multivariate calculus.
  • Strong understanding of classical ML techniques and time-series forecasting.
  • Understands data management principles along with model evaluation and training techniques for neural networks.
  • Conversant in Python and one or more programming languages such as Golang, Java, or Scala
  • Enjoys working in a geographically distributed environment
  • Ability to create models to pull valuable insights from data.
  • Create stories and visualizations to describe and communicate data insights.
  • Ability to use creativity to spot trends and tease out patterns in large datasets.
  • Strong analytical and problem-solving skills.
  • Excellent written and verbal communication skills; mastery in English and local language.

 

Preferred:

  • Experience in one or more deep learning frameworks such as Tensorflow/Keras, or PyTorch.
  • In-depth knowledge of one or more deep learning areas such as computer vision or natural language processing
  • History of contributions to open source projects such as projects hosted on GitHub, SourceForge, or OSDN.
  • Prior participation in data science competitions such as Kaggle, DrivenData, or CodaLab.

Scope & Impact

  • Collaborates with peers, junior engineers, data scientists, and project team.
  • Typically interacts with high-level Individual Contributors, Managers, and Program Teams.
  • Leads a project requiring data engineering solutions development.

Education & Experience

  • Master’s or PhD degree in Computer Science, Mathematics, Economics, Physics, or equivalent.
  • Typically 4-6 years’ experience including graduate or postgraduate research.

HP is the world’s leading personal systems and printing company. We create technology that makes life better for everyone, everywhere. Our innovation springs from a team of individuals, each collaborating and contributing their own perspectives, knowledge, and experience to advance the way the world works and lives.

At HP 200A (named after Hewlett-Packard’s first product – the HP200A audio oscillator), we are driving the strategic direction for our new, microfluidics-based, growth businesses… beginning with healthcare diagnostics. As the world’s largest microfluidics company with 30+ years of inkjet printing experience, we have the expertise and scale to craft sophisticated microfluidics solutions that can disrupt healthcare diagnostics.

Responsibilities

  • Leads organization wide creation of data science structure for system performance, customer behaviors, and channel / market insights across complex microfluidics based projects in life science disease diagnostic markets.
  • Defines and implements models to uncover patterns and predictions creating business value and innovation using modern tools & programming languages.
  • Manages and creates relationships with business partners to evaluate and foster data driven innovation, provide domain-specific expertise in cross-organization projects/initiatives.
  • Collaborates with R&D and Product Management to make sure system data is generated, captured, and that value based data driven business models are developed. Including business models leveraging data streams.
  • Communicating business value and innovation potential through effective insights/visualizations.
  • Represents the business at data science events, forums, boards.
  • Prepares and presents literature, presentations, invention disclosures for peer review & publication in industry data science domain initiatives and conferences.
  • Assures insights are communicated regularly and effectively, reviewing designs, models and accuracy and data compliance.
  • Defines, communicates and drives data insights/innovation into the business.
  • Leverages recognized domain expertise, business acumen, and overall data systems leadership to influence decisions of executive business leadership, development partners, and industry standards groups.
  • Provides guidance, training and mentoring to less experienced staff members.

Knowledge & Skills

  • Extensive experience using statistics, mathematics, algorithms and programming languages to solve big data challenges.
  • Demonstrated innovation in the domain including creating new capabilities from scratch and educating organizations on data opportunities/insights.
  • Fluent in structured and unstructured data, its management, and modern data transformation methodologies.
  • Ability to define and create complex models to pull valuable insights, predictions and innovation from data.
  • Effectively and creatively tell stories and create visualizations to describe and communicate data insights.
  • Strong analytical and problem-solving skills.
  • Excellent written and verbal communication skills; mastery in English and local language.
  • Ability to effectively communicate data product architectures and/or algorithm design proposals and negotiate options at senior management levels, BU and executive levels.

Scope & Impact

  • Collaborates with peers, junior engineers, data scientists and project team including marketing and finace.
  • Typically interacts with high- level Individual Contributors, Managers, Directors and Program Core Teams.
  • Leads multiple projects requiring data engineering solutions development.
  • Drives design innovation.

Education & Experience

  • Bachelor’s, Master’s or PHD degree in Mathematics, Economics, Physics, Computer Science, data science, Statistics, Analytics or equivalent.
  • Typically 10+ years’ experience including graduate or postgraduate research.
  • Advanced Excel/Data base capabilities
  • Coding knowledge and experience with several languages
  • Knowledge and experience in statistical and data mining techniques

Towers Crescent (12066), United States of America, Vienna, Virginia

Principal Associate Data Science, Customer Identity

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

Digital ML is the data science and machine learning team inside Capital One’s Digital Products organization.  We deliver real-time, personalized, intelligent customer experiences in Capital One’s suite of award-winning digital products, including our website, mobile app, emails, chatbot, and beyond.  We partner closely with our product and engineering teams to build the data and modeling platforms crucial to delighting a combined 52 million customers each month and empowering them to manage their financial lives digitally.

As part of Digital ML, you will work on things like:

  • The servicing optimization engine that anticipates customers’ needs in real time and helps them manage their accounts, purchases, payments, rewards, and more
  • The marketing optimization engine that selects the right offer for the right customer
  • The experimentation engine that enables us to rigorously test new features, messaging and offers for our customers
  • Customer behavioral analyses (using transaction, clickstream and other data) that identify trends, patterns and relationships related to product usage

Role Description

In Digital ML, you will work at all phases of the data science lifecycle, including:

  • Build machine learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams to operationalize them in scalable and resilient production systems that serve 50+ million customers.
  • Partner closely with a variety of business and product teams across Capital One to conduct the experiments that guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention.
  • Write software (Python, Scala, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark and AWS.

The Ideal candidate will be:

  • Curious and creative.  You thrive on bringing definition to big, undefined problems.  You love asking questions, and you love pushing hard to find the answers.  You’re not afraid to share a new idea.  You communicate clearly and effectively to share your findings with non-technical audiences.
  • Technical: You have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud computing platforms.  You are not afraid of petabytes of data.
  • Statistically-minded.  You have built models, validated them and backtested them.  You know how to interpret a confusion matrix or a ROC curve.  You have experience with clustering, classification, sentiment analysis, time series analysis and deep learning.
  • Customer and product oriented.  You share our passion for changing banking for good.

Basic Qualifications:

  • Bachelor’s Degree plus 5 years of experience in data analytics, or Master’s Degree plus 3 years in data analytics, or PhD
  • At least 1 year of experience in open source programming languages for large scale data analysis
  • At least 1 year of experience with machine learning
  • At least 1 year of experience with relational databases

Preferred Qualifications:

  • Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
  • At least 1 year of experience working with AWS
  • At least 3 years’ experience in Python, Scala, or R
  • At least 3 years’ experience with machine learning
  • At least 3 years’ experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

As a Data Scientist at Capital One, you’ll be part of a high-performing team that’s embracing the latest in computing technologies to unlock opportunities that help everyday people save money and improve their financial lives. You’ll help our customers solve their financial services challenges by using groundbreaking techniques.  You’ll make valuable contributions from day one by continuously learning, engaging in diverse sets of experiences and building close-knit relationships across the company.

On any given day, you might:

  • Evaluate open-source and internally-developed modeling and analytics tools using real business data
  • Integrate internal data with external data sources and APIs to discover and implement actionable insights
  • Design and craft rich data visualizations to communicate stories to customers and company leadership

We’d love to find someone who is…

  • Intellectually curious. You ask why, you explore, and you are excited to imagine and create new ideas by inventing self-adaptive models or by tapping into unstructured data sources. You love mining data for insights into behaviors, intent and sentiment
  • A builder. You are passionate about delivering better experiences and better products to our customers and have a deep sense of ownership for your craft.
  • An experimental scientist. You love putting on your lab coat and trying new things, new combinations of tools, techniques and feature engineering approaches even if you sometimes fail.

Are you ready to join a community of talented individuals who embrace customer problems and use their passion and capabilities to make a difference every single day? If you’re interested in a long-term career at Capital One, the Data Science internship could be a great way to begin your career journey!

Basic Qualifications: 

  • PhD degree obtained between December 2021 and August 2024
  • At least 6 months of experience or academic work in open source programming languages for data analysis

Preferred Qualifications: 

  • Direct experience with either Python or R, plus one other general-purpose programming language
  • Experience or academic work in inferential statistics
  • Experience or academic work in machine learning
  • Experience or academic with relational databases
  • Experience or academic with large scale data analysis

This is a paid internship. This is a limited-time internship position, and Capital One will not sponsor a new applicant for employment authorization for this position. However, a full-time Data Science role, for which you may be considered upon completion of the internship (subject to business need, market conditions, and other factors) is eligible for employer immigration sponsorship. 

No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

 

Team Description

Digital ML is the data science and machine learning team inside Capital One’s Digital Products organization.  We deliver real-time, personalized, intelligent customer experiences in Capital One’s suite of award-winning digital products, including our website, mobile app, emails, chatbot, and beyond.  We partner closely with our product and engineering teams to build the data and modeling platforms crucial to delighting a combined 52 million customers each month and empowering them to manage their financial lives digitally.

 

As part of Digital ML, you will work on things like:

  • The servicing optimization engine that anticipates customers’ needs in real time and helps them manage their accounts, purchases, payments, rewards, and more
  • The marketing optimization engine that selects the right offer for the right customer
  • The experimentation engine that enables us to rigorously test new features, messaging and offers for our customers
  • Customer behavioral analyses (using transaction, clickstream and other data) that identify trends, patterns and relationships related to product usage

 

Role Description

In Digital ML, you will work at all phases of the data science lifecycle, including:

  • Build machine learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams to operationalize them in scalable and resilient production systems that serve 50+ million customers.
  • Partner closely with a variety of business and product teams across Capital One to conduct the experiments that guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention.
  • Write software (Python, Scala, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark and AWS.

 

The Ideal candidate will be:

  • Curious and creative.  You thrive on bringing definition to big, undefined problems.  You love asking questions, and you love pushing hard to find the answers.  You’re not afraid to share a new idea.  You communicate clearly and effectively to share your findings with non-technical audiences.
  • Technical: You have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud computing platforms.  You are not afraid of petabytes of data.
  • Statistically-minded.  You have built models, validated them and backtested them.  You know how to interpret a confusion matrix or a ROC curve.  You have experience with clustering, classification, sentiment analysis, time series analysis and deep learning.
  • Customer and product oriented.  You share our passion for changing banking for good.

 

Basic Qualifications:

  • Bachelor’s Degree plus 2 years of experience in data analytics, or Master’s Degree, or PhD
  • At least 1 year of experience in open source programming languages for large scale data analysis
  • At least 1 year of experience with machine learning
  • At least 1 year of experience with relational databases


Preferred Qualifications:

  • Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
  • Experience working with AWS
  • At least 2 years’ experience in Python, Scala, or R
  • At least 2 years’ experience with machine learning
  • At least 2 years’ experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

ob Summary

The Erik Jonsson School of Engineering and Computer Science at The University of Texas at Dallas (UT Dallas) invites applications for an Assistant Professor tenure-system position in all areas of Materials Science and Engineering. The Materials Science and Engineering Department at UT Dallas has 13 faculty members, approximately 80 graduate student and offers MS and PhD degrees in Materials Science and Engineering. Areas of research expertise include advanced micro- and nanoelectronics, catalysis, sensing, biomedical devices, flexible electronics, and energy storage and conversion. Particular emphasis will be placed upon candidates at the Assistant Professor level who have research expertise in advanced electronic materials, nano-characterization, energy storage and conversion, and accelerated materials design via computational methods. The candidate will be expected to build an active research program. Qualified candidates must have a strong commitment to undergraduate and graduate education, and the potential to develop an externally funded research program.

Located in the 4th largest metropolitan area in the US, The University of Texas at Dallas is a young, growing research institution on the cutting edge of science, technology, medicine, business, and arts. Since its conception by Texas Instruments’ founders McDermott, Jonsson, and Green, the University’s teaching mission has continuously expanded, its external research funding has nearly doubled in recent years, and the University has established itself as a national leader in research. A facility of particular relevance for the faculty position is the $85 million landmark Natural Science and Engineering Research Laboratory (NSERL) that hosts a fully furnished clean room.

To apply for this position, applicants should submit a letter of application; current curriculum vitae; statement of research and teaching interests; teaching evaluations (if available) and the full contact information for at least three academic or professional references. Applications received by February 28, 2021 will receive full consideration. UT Dallas strongly encourages applications from candidates who would enhance the diversity of the University’s faculty.

For further information please contact:
msefacultysearch2021@lists.utdallas.edu

Minimum Education and Experience

An earned graduate degree appropriate to the academic discipline and a record of productivity and professional achievement.

Preferred Education and Experience

An earned doctorate in Materials Science, or related field with research in Engineering areas. Related fields include Mechanical Engineering, Material Science, Electrical Engineering, Computer Science, Mathematics, or Physics.

Areas of research expertise include advanced micro- and nanoelectronics, catalysis, sensing, biomedical devices, materials design, flexible electronics, and energy storage and conversion.

Essential Duties and Responsibilities

Demonstrate a commitment to teaching excellence

Prepare and teach undergraduate and/or graduate classes

Contribute assessment information and data as requested
Mentor and/or advise undergraduate and/or graduate students

Establish and/or continue an independent line of research

Continue to expand professional influence in the academic discipline through research and/or publication

Engage in service within the academic unit, the university, and the profession as appropriate based on teaching and research constraints

Physical Activities Working Conditions Additional Information Special Instructions Summary Important Message

1) All employees serve as a representative of the University and are expected to display respect, civility, professional courtesy, consideration of others and discretion in all interactions with members of the UT Dallas community and the general public.

2) UT Dallas does not discriminate on the basis of race, color, religion, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, national origin, disability, genetic information, or veteran status in its programs and activities, including in admission and enrollment. For inquiries regarding non-discrimination policies, contact the Director of Institutional Equity at InstitutionalEquity@utdallas.edu or the Title IX Coordinator at TitleIXCoordinator@utdallas.edu, or call 972-883-5331.

We are a Cambridge, MA based biotechnology company developing drugs based on engineered probiotic and food strain bacteria for the treatment of Inflammatory Bowel Disease. We are looking for a motivated hard working PhD scientist with expert background in gram-positive bacterial genetics, preferably a proven track record in lactic acid bacterial engineering. Prior industry experience is not required, and this can be an opportunity to get to know the dynamic and goal-oriented world of biotech and make contacts within the industry. This will be a hands-on position doing bench research and closely collaborating within a multidisciplinary team of scientists and research associates. The successful applicant will be an individual looking to grow in a dynamic and challenging environment, inventive and team oriented. The position includes benefits and a salary commensurate with experience. Candidates must be eligible for employment in the United States.

If you are interested in opportunities at ViThera Pharmaceuticals, please forward your CV or resume to info@vitherapharma.com.

Job Description

The Environmental Molecular Sciences Division seeks a Biomaterial Scientist focused on understanding the role of the soil microbiome on fundamental biogeochemical processes. This position involves the development of microfabricated soil-like devices, and their use to gain a mechanistic understanding of how the soil microenvironment influences the soil microbiome, and in turn how that regulates biogeochemical events at the ecosystem scale. This position will provide an opportunity to work with a diverse team of scientists to understand the molecular processes that regulate soil microbial ecology and ecosystem biogeochemistry. In addition, the individual will be expected to expand the Environmental Molecular Sciences Laboratory capabilities within this scope in effort to attract an active user community.

Aside from using the microfabrication capabilities (e.g., cleanroom, photolithography, 3D printing, etc.), the position will entail employment of many of the tools available within EMSL to elucidate both biotic and abiotic soil processes occurring within the soil emulating microfabricated devices. This includes, but is not limited to, the use of the state-of-the-art mass spectrometry and fluorescence microscopy capabilities. Experience in collaborating with other User Facilities for multimodal studies is desirable. The candidate should possess good oral and written communication skills and strong interpersonal skills. The applicant will be expected to contribute to ideas and methods expanding on existing R&D and may collaborate on reports, papers, posters, and presentations. The candidate must also demonstrate initiative, creativity and innovative thinking, and high tolerance for the ambiguity, dynamics, and diversity of work characteristic of a research environment.

EMSL is a national scientific user facility and research directorate located at Pacific Northwest National Laboratory (PNNL). EMSL is supported and stewarded by the U.S. Department of Energy’s (DOE) Office of Biological and Environmental Research (BER). The EMSL User facility is designed to provide innovative and breakthrough experimental and computational science that addresses BER programs by providing access to more than 75 state-of-the-art instrumental and computational capabilities. EMSL Users address some of the most important molecular-to-mesoscale challenges relevant to DOE missions.

Minimum Qualifications

BS/BA with 2 years of experience, MS/MA with 0-2 years of experience, or PhD with 0 years of experience.

Preferred Qualifications

  • PhD in Biology, Chemistry, Biochemistry, Material Science, Chemical Engineering or a related field.
  • 2 years of relevant postdoctoral experience or other relevant skills.
  • Direct experience and expertise in microfabrication, fluorescence microscopy, and microbiology.
  • Experience in using DOE User Facilities.