Multiple technology and digital health internships in IT/Data Science/ML/AI for summer and fall 2022
ReSurfX is an outcomes intelligence technology company ‘enabling better decisions and outcomes’ by improving innovation and ROI from data intensive activities of enterprises with focus on effective development of treatment options and patient care delivery in pharma, biotech and healthcare sectors. ReSurfX leverages a novel data-source agnostic machine learning approach ‘Adaptive Hypersurface Technology’ (AHT) we invented, to provide uniquely differentiated and powerful AI solutions including for automated knowledge extraction and advance prediction of outcomes directions. ReSurfX provides these values as enterprise software products as well as by improving measurement technologies at sensor and component levels. Our enterprise SaaS platform ReSurfX::vysen has ‘best-in-class’ functionalities including the remarkably powerful System Response based Triggers and Outcomes Predictor (SyRTOP).
We invite you to join ReSurfX and revolutionize at the leading edge of AI creating impactful solutions for important societal needs. Invent, analyze, design, build, scale, sell, maintain some of the best products by applying your technical and business knowledge and creativity including in information technology, machine learning, data sciences, marketing, sales, measurement technologies (instrumentation and assays), and specialized sector knowledge of healthcare, pharma, biotech. Send your information and interest to email@example.com with [Internship 2022] and the internship title of your primary interest included in Subject line of email.
ReSurfX internship program is unique as they are tailored to provide opportunity and training towards career and life goals of the team members and has been an excellent success. The diversity of intern team members across the spectrum of education, experience levels and roles who have passed through ReSurfX and successfully progression towards their goals can be seen in our website. As a multi-disciplinary company ReSurfX involves people from various sector and technical, market expertise. Our culture places immense care and values growth of each member towards their goal while accomplishing company growth. We strive to provide a fun loving culture and environment that also aids intense focus to provide the best products to the market and immense value to all stakeholders.
The summer internships for 2022 are remote. However candidates in reasonable traveling distance to our Cambridge, MA location will be preferred to maintain the possibility of meeting occasionally. ReSurfX technology internships for 2022 are interrelated with partially overlapping skillset requirements geared towards common goals. With perspectives that the different internships overlap and internships have a significant training component: (i) it will help to scan through multiple positions to find your fit as there is significant flexibility; and (ii) each position includes broad skillsets that intended to convey ‘components of’, ‘some combination of’ and ‘aimed towards’.
The internships are initially for three months between May 1st and December 30th – with start date ideally coordinated with other members starting around the same time.
The objectives for the internships will be application oriented and choice of projects will depend on prior exposure and future goals of the intern and aligned with interests of the company. Enthusiastic, motivated, collaborative and quick learning individuals with good communication and documentation skills will thrive and significantly elevate your career skills suited for success in most modern digital enterprises.
Machine Learning and Analytics Development
The Big Data Machine Learning Analytics Intern(s) will primarily be involved in applying a number of large volume data analytics and prediction tools for AI (ML and statistics and combinations) to particular public domain, simulated or provided datasets either as a technical problem or for specific application needs. The candidate will approach the datasets from data science perspective than focus on subject matter of their source. Apply contemporary and well established ML approaches and functionalities in use for related applications; participate in design and evaluating metrics of performance with results generated and those provided by other team members. This member will collaborate with team members from other specialties (SMEs) to learn about the datasets and relating the project goal to real life applications as well as with software development and implementation teams as needed.
ML approaches (including deep learning) and frameworks as well as fluency in Python (essential); creating ensembles, evaluation metrics, model tuning, optimization and stability testing; cloud based commoditized ML and statistical tools, large-volume (big data) analytic toolbox techniques; fluency in use of APIs cloud based execution of goals; expertise in use of tools for project tracking and documentation. Good understanding of principles behind the ML tools, statistics and database schema will be very advantageous.
Medicine and Life Science Machine Learning and Analytics
Apply a variety of ML and analytics tools for AI based solutions specifically using life science and medical datasets. This intern team member will have expertise in life science or medical sectors such as development or participation in one or more sector specific data collection, analysis and prediction using large datasets. The intern will evaluate a variety of ML and statistical approaches used in AI; setup and evaluate metrics; compile results generated (and those provided by other team members) and generate metrics of performance against real life end-use goals. This member will serve as the subject matter expert and collaborate with team members from other specialties – e.g., IT or data oriented skillsets.
Excellent knowledge with one or more of life sciences and healthcare data sources with prior experience with their use functional project(s) in those sectors; expertise in at least one scripting language; knowledge of data formats and structures; handling large volume data from specific platforms, standardized data formats and conversions, database schema. Fluency in at least one ML framework and Python is expected.
ML and Analytics Software Development and Engineering
The Big Data Analytics Software Engineering Intern(s) will be involved in some combination of modular development of components, integration of components of other products into workflows for large-volume data applications; sophisticated use of APIs; software and system performance analysis and optimization including compute, memory, and I/O resources; packaging modules for contemporary at-scale application implementation frameworks. Knowledge of ML tools and frameworks, ML application development, distributed code/product development principles, cloud based resources and automation tools for these needs will be advantageous.
Proficiency in one of more of programming languages C++ or Python (essential), R, familiarity with JAVA, PHP, html, css, knowledge of older style C/C++; OOP; knowledge of web application development as well as needs and tools for developing solutions for large-volume data; system and software performance analysis and optimization; tools for quality and performance testing, automated software and workflow deployment; excellent understanding of API development and usage; expertise in use of tools for project tracking and documentation; integration of components developed in different software programming languages across application frameworks and operating systems. This person will work closely with ML, implementation and Ops team as needed.
ML and Analytics Software Implementation
The Big Data Analytics Implementation Engineering Intern(s) will be involved with be involved with setting up and evaluating optimal modern Ops implementation strategies application functionalities for predominantly cloud-based web application software for large scale data use. This person will identify needs and participate in converting module(s) into optimal formats for integration (in collaboration with functionality development team members) and efficient orchestration of workflows with significant ML component. Excellent understanding and ideally hands-on experience with application and infrastructure components, Ops tools available across stacks in production and development of analytics and machine learning solutions is expected of this intern team member. The project will also include performance analysis and optimization and report creation on performance, security and audit.
Proficiency in Python (essential), C++, R, JAVA, PHP, html, css, knowledge of multi-tenant web applications, infrastructure and tools for deploying software and other ML solutions for large-volume data in predominantly cloud based applications for at-scale use; API integration for usage and large scale deployment; automated workflow deployment and performance monitoring, orchestration of implementation across software, deployment stack using Ops tools (DevOps and MLOps); expertise in use of tools for project tracking and documentation (essential); distributed code/product development practices, integration of components developed in different software programming languages across application frameworks and operating systems.
ML and Analytic Database Development and Implementation
The Big Data ML and Analytics Data Store Engineering Intern(s) will primarily be involved in the database tier used in analytics and AI products including extract-transform-load (ETL) capabilities for and query and integration of data with downstream processing. The term database is used in a loose sense, and also refers to contemporary variants involving data store(s) in different formats. The project will involve some combination of data collection, data quality analysis, data format conversions, schema creation and alterations, developing relevant queries and scripts, sophisticated use of APIs, data transactions in variety of formats and sources, orchestration and control of flow (as in DevOps or MLOps) between data stack and other layers.
Proficiency and experience with databases, schema development and modifications, scripting languages (SQL and Python are essential) and data structures; data stores, data pipelines, bottleneck analysis and remediation; API development and usage; well established and contemporary tools for data storage and transactions. Prior experience with large volume data usage in other application tiers will be a significant advantage.