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Algorithm Research Jobs in Edison, NJ (NOW HIRING)

Research Intern

New York, NY · On-site

$48K - $62K/mo

Description RESEARCH INTERNSHIP Department of Computer Science and Engineering New York University ... They should have a strong background in AI/ML, biometric algorithm design and evaluation, and ...

... algorithms for biomedical engineering applications * conducting human subject research including ... physiological health data collection * data analysis The successful candidate will have a ...

In this role, your time will be split between tackling open-ended research problems-such as designing novel architectures and improving algorithmic efficiency - and building the distributed training ...

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Algorithm Research information

Is ML a high paying job?

Machine Learning (ML) roles, including those in algorithm research, are generally well-paid due to the high demand for specialized skills in data analysis, programming, and statistical modeling. Salaries vary based on experience, location, and industry, but advanced ML positions often offer competitive compensation compared to other tech roles.

What is algorithmic research?

Algorithm research involves studying and developing new algorithms to solve computational problems efficiently. It requires understanding theoretical concepts, analyzing algorithm performance, and often involves programming and testing in environments like Python or C++. This work supports advancements in fields such as artificial intelligence, data analysis, and software development.

What are the key skills and qualifications needed to thrive as an Algorithm Researcher, and why are they important?

To excel as an Algorithm Researcher, you need a strong background in mathematics, computer science, and algorithm design, often supported by an advanced degree such as a master's or PhD. Proficiency with programming languages (like Python, C++, or Java), machine learning frameworks, and version control systems is essential. Analytical thinking, creativity, and effective communication are crucial soft skills that set top performers apart in this field. These skills are vital for developing innovative, efficient solutions and collaborating within interdisciplinary teams to solve complex computational problems.

Which 3 jobs will survive AI?

Algorithm research jobs are likely to persist because they involve developing new algorithms and understanding complex data, tasks that require human creativity and critical thinking. Roles in healthcare, such as medical professionals, and skilled trades like electricians or plumbers, are also expected to remain in demand due to the need for hands-on expertise and human judgment. These jobs often require specialized knowledge, certifications, or physical skills that are difficult for AI to replicate fully.

Is AI replacing algorithms?

Algorithm research involves developing and improving algorithms, which are fundamental to AI systems. AI often relies on algorithms to process data and make decisions, but it does not replace the need for algorithm development; instead, AI advances can lead to new algorithmic techniques and improvements. Researchers in this field focus on creating efficient, effective algorithms that support AI applications and other computational tasks.

What is Algorithm Research?

Algorithm research involves studying, designing, analyzing, and optimizing algorithms to solve complex problems efficiently. Researchers in this field explore new computational methods, improve existing algorithms, and evaluate their performance in various contexts. This work is fundamental in areas like computer science, artificial intelligence, data science, and cryptography, driving technological advances and innovation.

What are the typical challenges faced by professionals in Algorithm Research roles and how can they best address them?

Algorithm Research professionals often encounter challenges such as bridging the gap between theoretical solutions and practical implementation, staying updated with rapid advancements in the field, and collaborating with cross-functional teams to integrate research outcomes into real-world products. To address these challenges, it is helpful to maintain strong communication with engineering teams, participate in continual learning through academic papers and conferences, and adopt an iterative approach to testing and refining algorithms. Building a habit of documenting experiments and results also streamlines collaboration and future development.

What is the difference between Algorithm Research vs Data Scientist?

AspectAlgorithm ResearchData Scientist
Required CredentialsAdvanced degrees in CS, Mathematics, or related fieldsDegree in CS, Statistics, or related fields; certifications like SAS or Python
Work EnvironmentResearch labs, R&D departments, academiaBusiness environments, analytics teams, tech companies
Industry UsageDeveloping new algorithms, theoretical researchAnalyzing data, building predictive models, insights generation
Common Search/ComparisonYesNo

Algorithm Research focuses on developing and testing new algorithms, often in research or academic settings, requiring advanced technical credentials. Data Scientists analyze data to generate insights and build models, working primarily in business environments. While both roles involve data and programming, their core objectives and work settings differ significantly.

What job categories do people searching Algorithm Research jobs in Edison, NJ look for? The top searched job categories for Algorithm Research jobs in Edison, NJ are:
What cities near Edison, NJ are hiring for Algorithm Research jobs? Cities near Edison, NJ with the most Algorithm Research job openings:
Data Scientist I (Assistant)

Data Scientist I (Assistant)

AllSTEM Connections

Rahway, NJ • On-site

$104K - $114K/yr

Temporary

Medical, Dental, Vision, Retirement

Re-posted 16 days ago


Job description

Job Title: Assistant Data Scientist - Computational Drug Discovery & Molecular Modeling
Role Overview
We are seeking an intellectually curious and scientifically grounded Assistant Data Scientist to join our cutting-edge discovery therapeutics division. In this early-career role, you will sit at the vital interface of advanced computer science and molecular biology, deploying machine learning workflows and rigorous statistical analyses to help accelerate the discovery of next-generation medicines.
As an embedded member of a cross-functional scientific computing group, you will address complex data problems across multiple modalities. You will have a direct, hands-on influence on analyzing the data outputs of state-of-the-art automated equipment and high-throughput screening platforms. This role is designed for a highly analytical self-starter who wants to develop property-prediction models, explore deep learning architectures, and collaborate dynamically with laboratory biologists and chemists to identify therapeutic leads.
Key Responsibilities
Machine Learning Engineering & Molecular Modeling
• Workflow Automation: Develop, optimize, and maintain predictive machine learning and deep learning workflows that enable the discovery and design of novel small molecules and peptides.
• Property Prediction: Contribute to the architecture and scaling of molecular property prediction models to screen for target potency, selectivity, and metabolic viability.
• Algorithm Research: Conduct active computational research in areas of machine learning, molecular modeling, and virtual screening applications relevant to early-stage pipeline acceleration.
• Infrastructure Utilization: Leverage high-performance computing (HPC) clusters in a Unix/Linux environment or cloud architectures (AWS) to manipulate high-volume molecular and bioinformatics datasets.
Interdisciplinary Collaboration & Insights Delivery
• Cross-Functional Synergy: Partner closely with laboratory chemists, molecular biologists, and informatics specialists to apply modeling techniques that advance molecules from lead optimization to clinical candidates.
• Data Synthesis & Interpretation: Provide multi-disciplinary stakeholders with an in-depth understanding of complex data outputs, interpreting analytical results to guide the physical experimental design process.
• Hypothesis Generation: Apply rigorous computational methods to help wet-lab scientists generate novel, testable hypotheses for cellular target discovery and molecular mechanisms of action.
• Technical Presentation: Communicate highly complex mathematical or algorithmic results effectively and concisely to non-technical business partners in both written formats and formal oral presentations.
Qualifications & Requirements
Minimum Qualifications
• Education: Bachelor's degree in Computational Physics, Computational Chemistry, Bioinformatics, Computer Science, or a closely related quantitative, data-dense scientific field.
oCandidates possessing a Master's degree or PhD in these same quantitative disciplines are highly encouraged to apply.
• Experience Baseline: 0 to 3 years of hands-on data science or machine learning application experience (academic research, thesis work, or industry internships will be fully considered).
• Programming Fluency: Deep, hands-on proficiency in Python specifically tailored for scientific computing and deep learning frameworks (e.g., NumPy, PyTorch, SciPy, or Pandas).
• Systems Literacy: Proven experience navigating high-performance computing clusters in a Unix/Linux OS environment, or direct familiarity with scalable cloud computing architectures (specifically AWS).
• Domain Alignment: A foundational, working knowledge of biochemistry, organic chemistry, or molecular biology concepts.
Preferred "Nice-to-Have" Qualifications
• Direct experience participating in computational research projects within an early-stage pharmaceutical drug discovery or biotechnology space.
• Experience developing or fine-tuning large-scale chemical foundation models, virtual screening applications, or protein structure-related models (e.g., AlphaFold/RoseTTAFold variations).
• Exceptional priority-balancing habits and a demonstrated ability to build strong, collegial relationships across a multicultural matrix organization.
Equal Opportunity Employer / Disabled / Protected Veterans
The Know Your Rights poster is available here:
https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12.pdf
The pay transparency policy is available here:
https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf
For temporary assignments lasting 13 weeks or longer, AllSTEM Connections is pleased to offer major medical, dental, vision, 401k and any statutory sick pay where required.
We are committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation for any part of the employment process, please contact your staffing representative who will reach out to our HR team.
AllSTEM Connections participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program.
https://e-verify.uscis.gov/web/media/resourcesContents/E-Verify_Participation_Poster_ES.pdf
We also consider for employment qualified applicants regardless of criminal histories, consistent with legal requirements, including, if applicable, the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance. Pursuant to applicable state and municipal Fair Chance Laws and Ordinances, we will consider for employment-qualified applicants with arrest and conviction records, including, if applicable, the San Francisco Fair Chance Ordinance. For Los Angeles, CA applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Additional Skills
(none specified)
AllSTEM Representative Contact Info
Account Executive:
Nichols
Branch Phone:
(909) 244-1777
Location:
Ontario, CA