AKINODE LEKAN

Over 10years experience in Academics.
#MSc. (Uni of Hull,UK) .#Looking for a Funded PhD position in Comp Sci in 2024
Research Interest:ML,NLP and Blockchain

[Vikram Verma @VikramVerm25510]

50 Web Sites Google Doesn't Want You to Know About

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27.) 'https://t.co/TuT5TwfEpi' — Listen to any radio station worldwide
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The internet is much bigger than what Google shows you...

Cc : Respective author

[Suraj Sharma @suraj_sharma14]

If I had 6 months to become an Agentic AI Engineer.

I'd do this.

Stage 1: Python and LLM Foundations
Python, async, API design, Anthropic/OpenAI SDKs, tokens, embeddings, structured outputs.

Stage 2: Context Engineering
System prompts, few-shot patterns, chain-of-thought, context budgets, dynamic context assembly.

Stage 3: Tool Calling and Function Schemas
JSON schemas, Pydantic validation, retry logic, dynamic tool discovery, error recovery.

Stage 4: Agent Loop Patterns
ReAct, plan-and-execute, reflection, self-correction, max iteration limits.

Stage 5: One Agent Framework, Deeply
LangGraph state machines, nodes and edges, CrewAI roles, OpenAI Agents SDK handoffs.

Stage 6: Memory Systems
Short-term buffers, long-term vector recall, episodic summaries, context compression.

Stage 7: Agentic RAG
Hybrid search, reranking, parent document retrieval, query rewriting, citation tracking.

Stage 8: MCP and Integrations
MCP servers and clients, tool standardization, API connectors, webhooks, auth.

Stage 9: Multi-Agent Orchestration
Supervisor patterns, typed state handoffs, consensus logic, human-in-the-loop, escalation.

Stage 10: Evals and Observability
Golden datasets, trajectory evals, LLM-as-a-judge, LangSmith/Langfuse tracing, regression gates.

Stage 11: Production Deployment
Docker, CI/CD, guardrails, cost tracking, fallback chains, checkpoint and resume.

Stage 12: Public Portfolio
Ship 3 agents, publish architecture writeups, share benchmarks, record live demos.

Most people stay stuck watching tutorials.

Builders get hired.

(Bookmark & Repost !!!)

[Ajit kumar @ajitcodes]

Google just released a free 2-hour+ course on full agent engineering.

How to go from one prompt to a system that runs while you sleep:

38:46 - Build your first AI agent
54:46 - Connect MCP tools
1:12:43 - Run agents with four loop patterns
1:20:57 - Turn agent loops into graphs
2:22:31 - Build the complete autonomous system Most people are still building one agent and stopping there.

Google is already teaching the full stack:

Agents → Tools → Loops → Graphs → Autonomous Systems

Single agents are the old workflow.

Systems that run without you are the new one.

This course is worth more than most paid agent engineering bootcamps.

Bookmark and watch it today

Then read the full graph engineering playbook below

Free Ai Courses

𝟭. Generative AI: https://t.co/90mswzCE6q
𝟮. AI for Everyone: https://t.co/9Kb0s6WWGr
𝟯. ChatGPT for Excel: https://t.co/17ldGGrKSw

[AKINODE LEKAN @Lemmafire]

@DStvNg Hello ,I am trying to recomect my decoder amd I discovered that I have some outstanding om the account. Please explain this to me in a clear terms.

[Suraj Sharma @suraj_sharma14]

If I had 6 months to become an Applied AI Engineer.

I’d do this.

Stage 1: Python + Production APIs FastAPI, async, error handling, webhooks, REST/GraphQL, third-party SDKs.

Stage 2: LLM Fundamentals for Production Tokens, context windows, model routing, embeddings, cost/latency tradeoffs.

Stage 3: Prompt Engineering + Structured Outputs System prompts, few-shot chains, Pydantic/JSON validation, prompt versioning, unit evals.

Stage 4: RAG + Knowledge Grounding Chunking strategies, hybrid search, rerankers, vector DBs, metadata filtering, citation tracking.

Stage 5: AI Workflows + Orchestration Tool calling, state machines, human-in-the-loop, retry logic, fallback chains, session memory.

Stage 6: Build Production-Ready Apps Domain-specific copilots, automation pipelines, streaming UIs, graceful degradation, rate limiting.

Stage 7: Evaluation + Reliability Accuracy scoring, hallucination detection, RAGAS/DeepEval, regression testing, A/B output validation.

Stage 8: AI Infrastructure + Optimization vLLM, Ollama, quantization, KV caching, response streaming, token cost tracking, edge deployment.

Stage 9: Deployment + Observability Docker, CI/CD, cloud hosting, distributed tracing, structured logging, alerting, canary releases.

Stage 10: AI Security + Guardrails Input/output filtering, prompt injection defense, PII redaction, compliance checks, sandboxing.

Stage 11: Open Source + Portfolio Ship end-to-end apps publicly, write architecture docs, record demo walkthroughs, publish eval reports.

Stage 12: Apply Applied AI Engineer, GenAI Developer, AI Integration Engineer, LLM Solutions roles.

Most people stay stuck watching tutorials.

Builders get hired.

[Rahul @sairahul1]

Google Brain founder, Andrew Ng:

"100% of my tasks are done by ai agents, self-improving loops are next.

Give it 3-6 months and prompting is gone."

32 minutes of clear explanation on building loops from scratch.

Worth more than any $500 agentic course.

Watch it, then read the full guide below.

[AKINODE LEKAN @Lemmafire]

These guys @cosinewallet has solved a major issue in crytpo,eliminating gas fees for transactions !
This is commendable

[Denis Wirtz @deniswirtz]

Download our updated database of postdoc fellowships from different foundations and agencies.

We identified 275 fellowships. For each entry, we provide description of the fellowship, focus, amount, deadline, eligibility, etc.

Download this database here: https://t.co/EbTahdzbkp

[PhDScanner @PhdScanner]

🇬🇧 University of Edinburgh | PhD in Numerical Analysis for Stable AI 🤖📊

A PhD opportunity is open at the University of Edinburgh, focusing on the mathematical foundations of stable and trustworthy AI systems.

📌 Position Overview
🎓 Role: PhD Student
📍 Location: Edinburgh
🏢 Department: Numerical Analysis / AI Research
👨‍🏫 Supervisor: Des Higham
💰 Funding: ERC-funded studentship
⏳ Duration: PhD position (full-time)

🔬 Research Focus
This project investigates why modern AI systems can become unstable, biased, or vulnerable to adversarial attacks.

You will work on:
• Numerical analysis and applied linear algebra 📊
• AI robustness and adversarial stability
• Bias and fairness in machine learning systems
• Optimization, statistics, and high-dimensional analysis
• Scientific computing experiments using PyTorch 🤖

🎯 Goal: Develop mathematical insights and mitigation strategies for building safer and more reliable AI systems.

🌍 Research Environment
The project is part of the ERC-funded **NumAStAI** initiative, with collaborations across AI ethics, regulation, and generative AI research groups at Edinburgh.

🎯 Ideal Candidate
• Degree in Mathematics, Computer Science, or related field
• Strong quantitative and analytical skills
• Experience in scientific programming
• Interest in AI theory, stability, and trustworthy systems

🌟 Why Apply?
• Work on cutting-edge AI safety research 🚀
• Collaborate with leading researchers and visiting experts
• Opportunities for conferences and international research visits
• Interdisciplinary exposure to ethics and AI governance

🌍 Location
Edinburgh is one of Europe’s top academic cities, known for world-class research and a vibrant international community.

🔗 More Info
https://t.co/t14CxmyarB

#PhD #ArtificialIntelligence #MachineLearning #AIResearch #NumericalAnalysis #AIEthics #UniversityOfEdinburgh #Research

[Nana Yaw @GoScholari]

💻🎓 Fully Funded MS in Computer Science – Illinois State University 🇺🇸

Illinois State University offers a funded Master’s in Computer Science with graduate assistantships available.

✅ 100% tuition waiver
✅ Monthly stipend
✅ Open to international students

📍 Normal, Illinois, USA
⏳ Deadline: October

🔗 https://t.co/YnWSsY98hh

Find more funded CS opportunities 👇🏾
https://t.co/pursEFinfC 🇬🇭

#ComputerScience #MSCS #FullyFunded #StudyAbroad #GoScholar

[Scholarships and Jobs in Europe, US, Canada, AU... @Scholarshipps]

Ultimate ETH Zurich Vacancies: Updated PhD & Postdoc Jobs
ETH Zurich is a world-renowned center for science and technology. It continues to lead global rankings, particularly in Computer Science, Engineering, and Physical Sciences. For researchers, it offers an environment defined by extreme precision, massive computing power (including the Swiss AI Initiative), and some of the highest academic salaries in the world.
https://t.co/gR9CAnOFQJ

[ShaiGuides @shaiguides]

If you’re interested in pursuing a funded PhD or Master’s in Computer Science, Cybersecurity, AI, IT, or related fields, here are some schools worth checking out 👇

🇺🇸 USA
• North Carolina State University
• Virginia Tech
• University of Central Florida
• Clemson University

[Jack @jackcoder0]

Don't copy and paste answers from ChatGPT.

ChatGPT writing is easily detectable.

Use these prompts instead and see the magic:

[Research Radar @FellowshipRadar]

PhD alert ⚛️ 2–3 fully funded positions in superconducting quantum computing at the Niels Bohr Institute. Work on qubits, QEC & next-gen processors. Deadline: May 10, 2026. #PhD #QuantumComputing #Physics #Scholarships

https://t.co/FRPSHhRptV

[@mrajiabdulwasiu @mrajiabdulwasiu]

Funded PhD positions at the School of Engineering, University of Kansas, United States 🇺🇸.

Application cycle: Fall 2026 or Spring 2027.

[Felo @Anifelconsult]

contact Dr Duckbong Kim ([email protected]) to discuss their interests and possibilities. Tuition, stipend for PhD ($2,400-3,000/month) student and travel for conferences will be financially supported. Stipend/salary for post-doc ($50,000 to 60,000) and travel for conferences will be

[Cosmos Scholarship Network @ObengCosmos]

BioComp Group in the Department of Mathematics at Rowan University invites applications from motivated PhD students for Fall 2026 and Spring 2027 admission. Fully funded positions are available for outstanding candidates, including tuition support and stipend.

[Mrs M @MrsScotty_M]

There are several PhD student positions open at the centre for mathematical sciences at Lund University, funded by the strategic research area ELLIIT.
This is the link for more information at https://t.co/8DmEee2dCC

It is one of two PhD positions within the project "Next Generation Spatial AI" - a joint project between Lund University and Linköping University. Lot's of interesting possibilities to learn about both classical and modern data-driven methods for 3D understanding (structure from motion, structure from sound) with a fantastic team of researchers from both universities. Apply before 15 May 2026.

[PhDScanner @PhdScanner]

🇬🇧 Cancer Research UK | PhD in Generative AI for Biomedicine 🤖🧬

🚨 Deadline: June 8, 2026

A fully funded PhD studentship is available at Cancer Research UK, based at the Cambridge Institute, focusing on cutting-edge generative AI for biomedical discovery.

📌 Position Overview
🎓 Role: PhD Student
📍 Location: Cambridge
🏢 Department: Cancer Biology (CRUK Cambridge Institute)
👩‍🏫 Supervisor: Hana Aliee
💰 Salary: £22,500/year (fully funded)
⏳ Duration: 4 years
📅 Start: January 2027

🔬 Research Focus
This PhD explores how generative machine learning models can drive foundational discoveries in biology and medicine.

The project aims to develop probabilistic generative models and causal frameworks to better understand complex biological systems—such as why cells respond differently to treatments or how genetic changes influence outcomes.

Research areas include diffusion models, graph neural networks, causal ML, multimodal data integration, and dynamical systems (neural ODEs/SDEs)—bridging advanced AI with real-world biomedical challenges.

🛠️ Key Responsibilities
Develop novel generative models, improve interpretability and causal reasoning, integrate biological knowledge into AI systems, collaborate across disciplines, and publish in leading venues.

🎯 Ideal Candidate
Background in computer science, mathematics, or related field. Strong machine learning and programming skills, with interest in applying AI to biology or medicine. Prior biology knowledge is not required.

🌟 Why Apply?
Work at a world-leading biomedical research institute, tackle fundamental questions in health and disease, collaborate with top researchers, and gain interdisciplinary expertise at the intersection of AI and life sciences.

🌍 Location
Cambridge is a global hub for research and innovation, offering a vibrant academic environment and strong industry connections.

🔗 More Info
https://t.co/AUlhH2o4p8

#PhD #UK #ArtificialIntelligence #MachineLearning #Biomedicine #CancerResearch #DataScience #Research